Contents
Understanding Crowded Environments
- Robust Zero-Shot Crowd Counting and Localization with Adaptive Resolution SAM.
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In: European Conference on Computer Vision (ECCV), Milano, Oct 2024. - Boosting 3D Single Object Tracking with 2D Matching Distillation and 3D Pre-training.
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In: European Conference on Computer Vision (ECCV), Milano, Oct 2024. - Mahalanobis Distance-based Multi-view Optimal Transport for Multi-view Crowd Localization.
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In: European Conference on Computer Vision (ECCV), Milano, Oct 2024. [Project&Code] - Learning Tracking Representations from Single Point Annotations.
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In: CVPR Workshop on Learning With Limited Labelled Data for Image and Video Understanding (L3D-IVU), Jun 2024. - Generalized Characteristic Function Loss for Crowd Analysis in the Frequency Domain.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 46(5):2882-2899, May 2024 (online Nov 2023). [supplemental] - A Fixed-Point Approach to Unified Prompt-Based Counting.
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In: AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Feb 2024. [supplemental | code] - Multi-view People Detection in Large Scenes via Supervised View-wise Contribution Weighting.
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In: AAAI Conference on Artificial Intelligence (AAAI), Feb 2024. [Project&Code] - Single-Frame-Based Deep View Synchronization for Unsynchronized Multicamera Surveillance.
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IEEE Trans. on Neural Networks and Learning Systems (TNNLS), 34(12):10653-10667, Dec 2023. [code&dataset] - Modeling Noisy Annotations for Point-Wise Supervision.
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IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), 45(12):15065-15080, Dec 2023 (online Jul 2023). - Scalable Video Object Segmentation with Simplified Framework.
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In: International Conf. Computer Vision (ICCV), Paris, Oct 2023. [code] - DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks.
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In: IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), Jun 2023. [code] - Optimal Transport Minimization: Crowd Localization on Density Maps for Semi-Supervised Counting.
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In: IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), Jun 2023 (highlight). [code] - A Lightweight and Detector-Free 3D Single Object Tracker on Point Clouds.
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IEEE Trans. on Intelligent Transportation Systems, 24(5):5543-5554, May 2023. - 3D Crowd Counting via Geometric Attention-guided Multi-View Fusion.
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International Journal of Computer Vision (IJCV), 130:3123-3139, Dec 2022. - Scale-Prior Deformable Convolution for Exemplar-Guided Class-Agnostic Counting.
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In: British Machine Vision Conference, Nov 2022. - Calibration-free Multi-view Crowd Counting.
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In: European Conference on Computer Vision (ECCV), Tel Aviv, Oct 2022. [supplemental] - Wide-Area Crowd Counting: Multi-View Fusion Networks for Counting in Large Scenes.
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International Journal of Computer Vision (IJCV), 130(8):1938-1960, Aug 2022. - Crowd Counting in the Frequency Domain.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2022. - Kernel-based Density Map Generation for Dense Object Counting.
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IEEE Trans. Pattern Analysis and Machine Intelligence (TPAMI), 44(3):1357-1370, Mar 2022. - Dynamic Momentum Adaptation for Zero-Shot Cross-Domain Crowd Counting.
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In: ACM Multimedia (MM), Oct 2021. - BEV-Net: Assessing Social Distancing Compliance by Joint People Localization and Geometric Reasoning.
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In: Intl. Conference on Computer Vision (ICCV), Oct 2021. - Meta-Graph Adaptation for Visual Object Tracking.
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In: IEEE International Conference on Multimedia and Expo (ICME), Jul 2021 (oral). - A Generalized Loss Function for Crowd Counting and Localization.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2021. [supplemental] - Cross-View Cross-Scene Multi-View Crowd Counting.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR):557-567, Jun 2021. [supplemental | dataset] - Progressive Unsupervised Learning for Visual Object Tracking.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2021 (oral). [supplemental] - Fine-Grained Crowd Counting.
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IEEE Trans. on Image Processing (TIP), 30:2114-2126, Jan 2021. [code | data] - Tracking-by-Counting: Using Network Flows on Crowd Density Maps for Tracking Multiple Targets.
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IEEE Trans. on Image Processing (TIP), 30:1439-1452, 2021. - Visual Tracking via Dynamic Memory Networks.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 43(1):360-374, Jan 2021. [code] - Modeling Noisy Annotations for Crowd Counting.
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In: Neural Information Processing Systems (NeurIPS), Dec 2020. [supplemental] - Incorporating Side Information by Adaptive Convolution.
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International Journal of Computer Vision (IJCV), 128:2897-2918, July 2020. - ROAM: Recurrently Optimizing Tracking Model.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, Jun 2020. [code] - 3D Crowd Counting via Multi-View Fusion with 3D Gaussian Kernels.
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In: AAAI Conference on Artificial Intelligence, AAAI, New York, Feb 2020. [supplemental] - Adaptive Density Map Generation for Crowd Counting.
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In: Intl. Conf. on Computer Vision (ICCV), Seoul, Oct 2019. - Residual Regression with Semantic Prior for Crowd Counting.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , Long Beach, June 2019. [code] - Wide-Area Crowd Counting via Ground-Plane Density Maps and Multi-View Fusion CNNs.
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In: IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), Long Beach, June 2019. [dataset&code] - Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking.
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IEEE Trans. on Circuits and Systems for Video Technology (TCSVT), 29(5):1408-1422, May 2019. - Learning Dynamic Memory Networks for Object Tracking.
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In: European Conference on Computer Vision (ECCV), Munich, Sept 2018. [code] - Crowd Counting by Adaptively Fusing Predictions from an Image Pyramid.
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In: British Machine Vision Conference (BMVC), Newcastle, Sept 2018. [supplemental] - Fusing Crowd Density Maps and Visual Object Trackers for People Tracking in Crowd Scenes.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Jun 2018. - Incorporating Side Information by Adaptive Convolution.
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In: Neural Information Processing Systems, Long Beach, Dec 2017. [supplemental] - Recurrent filter learning for visual tracking.
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In: ICCV 5th Visual Object Tracking Challenge Workshop VOT2017, Venice, Oct 2017. [video] - Counting People Crossing a Line using Integer Programming and Local Features.
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IEEE Trans. on Circuits and Systems for Video Technology (TCSVT), 26(10):1955-1969, Oct 2016. [appendix] - Small Instance Detection by Integer Programming on Object Density Maps.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Boston, Jun 2015. [extended abstract] - Leveraging Long-Term Predictions and Online Learning in Agent-Based Multiple Person Tracking.
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IEEE Trans. on Circuits and Systems for Video Technology (TCSVT), 25(3):399-410, Mar 2015. - Surveillance of Crowded Environments: Modeling the Crowd by its Global Properties.
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In Modeling, Simulation and Visual Analysis of Crowds: A Multidisciplinary Perspective, Springer, New York, Dec 2013. - Crossing the Line: Crowd Counting by Integer Programming with Local Features.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Portland, Jun 2013. - Counting People with Low-Level Features and Bayesian Regression.
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IEEE Trans. on Image Processing (TIP), 21(4):2170-2177, May 2012. - Bayesian Poisson Regression for Crowd Counting.
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In: IEEE Intl Conf. on Computer Vision (ICCV), Kyoto, Sep 2009. - Analysis of Crowded Scenes using Holistic Properties.
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In: 11th IEEE Intl. Workshop on Performance Evaluation of Tracking and Surveillance (PETS 2009), Miami, Jun 2009. - Privacy Preserving Crowd Monitoring: Counting People without People Models or Tracking.
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In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, Jun 2008.
Explainable AI (XAI)
- Human attention guided explainable artificial intelligence for computer vision models.
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Neural Networks, 177:106392, Sep 2024. - Gradient-based Visual Explanation for Transformer-based CLIP.
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In: International Conference on Machine Learning (ICML), Vienna, Jul 2024. - Do large language models resolve semantic ambiguities in the same way as humans? The case of word segmentation in Chinese sentence reading.
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In: Annual Conference of the Cognitive Science Society (CogSci), Rotterdam, Jul 2024. - Demystify Deep-learning AI for Object Detection using Human Attention Data.
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In: Annual Conference of the Cognitive Science Society (CogSci), Rotterdam, Jul 2024. - Gradient-based Instance-Specific Visual Explanations for Object Specification and Object Discrimination.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), to appear 2024. - Towards the next generation explainable AI that promotes AI-human mutual understanding.
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In: NeurIPS workshop on XAI in Action: Past, Present, and Future Applications, New Orleans, Dec 2023. - Human Attention-Guided Explainable AI for Object Detection.
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In: Annual Conference of the Cognitive Science Society, July 2023. [arXiv] - ODAM: Gradient-based Instance-Specific Visual Explanations for Object Detection.
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In: Intl. Conf. on Learning Representations (ICLR), Rwanda, May 2023. [code]
Image Analysis
- A Secure Image Watermarking Framework with Statistical Guarantees via Adversarial Attacks on Secret Key Networks.
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In: European Conference on Computer Vision (ECCV), Milano, Oct 2024. - Group-based Distinctive Image Captioning with Memory Difference Encoding and Attention.
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International Journal of Computer Vision (IJCV), to appear 2024. - On Distinctive Image Captioning via Comparing and Reweighting.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 45(2):2088-2103, Feb 2023 (online 2022). - On Diversity in Image Captioning: Metrics and Methods.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 44(2):1035-1049, Feb 2022. - Group-based Distinctive Image Captioning with Memory Attention.
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In: ACM Multimedia (MM), Oct 2021 (oral). [supplemental] - Neighbours Matter: Image Captioning with Similar Images.
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In: British Machine Vision Conference (BMVC), Sep 2020. - Compare and Reweight: Distinctive Image Captioning Using Similar Images Sets.
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In: European Conference on Computer Vision (ECCV), Aug 2020 (oral). - Is that my hand? An egocentric dataset for hand disambiguation.
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Image and Vision Computing, 89:131-143, Sept 2019. [dataset] - Hand Detection using Zoomed Neural Networks.
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In: Intl. Conf. on Image Analysis and Processing (ICIAP), Trento, Sep 2019. - Describing like Humans: on Diversity in Image Captioning.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , Long Beach, June 2019. [code] - Hand detection using deformable part models on an egocentric perspective.
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In: Digital Image Computing: Techniques and Applications (DICTA), Canberra, Dec 2018. - Gated Hierarchical Attention for Image Captioning.
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In: Asian Conference on Computer Vision (ACCV), Perth, Dec 2018. [code] - CNN+CNN: Convolutional Decoders for Image Captioning.
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In: IEEE Computer Vision and Pattern Recognition: Language and Vision Workshop, Salt Lake City, Jun 2018. [code] - Efficient tree-structured SfM by RANSAC generalized Procrustes analysis.
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Computer Vision and Image Understanding (CVIU), 157:179-189, April 2017. - Enhanced Figure-Ground Classification with Background Prior Propagation.
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IEEE Trans. on Image Processing (TIP), 24(3):873-885, Mar 2015. - Look Closely: Learning Exemplar Patches for Recognizing Textiles from Product Images.
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In: Asian Conference on Computer Vision (ACCV), Singapore, Nov 2014. - Adaptive Figure-Ground Classification.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Providence, Jun 2012. - Supervised learning of semantic classes for image annotation and retrieval.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 29(3):394-410, Mar 2007. - Using Statistics to Search and Annotate Pictures: an Evaluation of Semantic Image Annotation and Retrieval on Large Databases.
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In: Proceedings of the American Statistical Association, Seattle, Aug 2006.
Eye Gaze Analysis
- Is Holistic Processing Associated with Face Scanning Pattern and Performance in Face Recognition? Evidence from Deep Neural Network with Hidden Markov Modeling.
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In: Annual Conference of the Cognitive Science Society (CogSci), Rotterdam, Jul 2024. - Eye Movement Behavior during Mind Wandering across Different Tasks in Interactive Online Learning.
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In: Annual Conference of the Cognitive Science Society (CogSci), Rotterdam, Jul 2024. - Use of online therapy session data to develop behavioural markers for cognitive outcomes in non-pharmacological intervention.
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In: Alzheimer's Association International Conference (AAIC), Amsterdam, July 2023. - Visual attention to own- vs. other-race faces: Perspectives from learning mechanisms and task demands.
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British Journal of Psychology, 114(S1):17-20, May 2023. - On Becoming Socially Anxious: Toddlers’ Attention Bias to Fearful Faces.
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Developmental Psychology, 59(2):353-363, Feb 2023. - Understanding the role of eye movement consistency in face recognition and autism through integrating deep neural networks and hidden Markov models.
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npj Science of Learning, 7:28, Oct 2022. - Understanding children's attention to traumatic dental injuries using eye-tracking.
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Dental Traumatology, 38(5):410-416, Oct 2022. - Understanding children’s attention to dental caries through eye-tracking.
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Caries Research, 56(2):129-137, June 2022. - Eye movement analysis of children's attention for midline diastema.
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Scientific Reports, 12:7462, May 2022. - The effects of attentional and interpretation biases on later pain outcomes among younger and older adults: A prospective study.
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European Journal of Pain, 26(1):181-196, Jan 2022. - Understanding the collinear masking effect in visual search through eye tracking.
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Psychonomic Bulliten & Review, 28(6):1933-1943, Dec 2021. - Do portrait artists have enhanced face processing abilities? Evidence from hidden Markov modeling of eye movements.
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Cognition, 211(104616), June 2021. - Eye Movement analysis with Hidden Markov Models (EMHMM) with co-clustering.
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Behavior Research Methods, 53:2473-2486, April 2021. - Understanding visual attention to face emotions in social anxiety using hidden Markov models.
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Cognition and Emotion, 34(8):1704-1710, Dec 2020. - The interrelation between interpretation biases, threat expectancies and pain-related attentional processing.
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European Journal of Pain, 24(10):1956-1967, Nov 2020. - Interpretation biases and visual attention in the processing of ambiguous information in chronic pain.
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European Journal of Pain, 24(7):1242-1256, Aug 2020. - The role of eye movement consistency in learning to recognise faces: Computational and experimental examinations.
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In: 42nd Annual Conference of the Cognitive Science Society (CogSci), Jul 2020. - Eye movement analysis with switching hidden Markov models.
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Behavior Research Methods, 52:1026-1043, June 2020. [appendix] - Understanding Individual Differences in Eye Movement Pattern During Scene Perception through Co-Clustering of Hidden Markov Models.
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In: The Annual Meeting of the Cognitive Science Society (CogSci), Montreal, Jul 2019. - Hidden Markov modelling of eye movements in social anxiety: a data-driven machine-learning approach to eye-tracking research in psychopathology.
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In: 2019 Anxiety & Depression Conference, Chicago, March 2019. - Individuals with Insomnia Misrecognize Angry Faces as Fearful Faces While Missing the Eyes: An Eye-Tracking Study.
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SLEEP, 42(2), zsy220, Feb 2019. - Eye Movement Patterns in Face Recognition are Associated with Cognitive Decline in Older Adults.
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Psychonomic Bulletin & Review, 25(6):2200-2207, Dec 2018. - Music Reading Expertise Facilitates English but not Chinese sentence reading: Evidence from Eye Movement Behavior.
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In: 15th International Conference on Music Perception and Cognition (ICMPC15), Sydney, July 2018. - Scanpath modeling and classification with Hidden Markov Models.
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Behavior Research Methods, 50:362-379, Feb 2018. - Is having similar eye movement patterns during face learning and recognition beneficial for recognition performance? Evidence from hidden Markov modeling.
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Vision Research, 141:204-216, Dec 2017. - Hidden Markov model analysis reveals the advantage of analytic eye movement patterns in face recognition across cultures.
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Cognition, 169:102-117, Dec 2017. - Insomniacs Misidentify Angry Faces as Fearful Faces Because of Missing the Eyes: an Eye-Tracking Study.
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In: The Annual Meeting of the Cognitive Science Society (CogSci), London, July 2017. - Mind reading: Discovering individual preferences from eye movements using switching hidden Markov models.
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In: The Annual Meeting of the Cognitive Science Society (CogSci), Philadelphia, Aug 2016. - Analytic Eye Movement Patterns in Face Recognition are Associated with Better Performance and more Top-down Control of Visual Attention: an fMRI Study.
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In: The Annual Meeting of the Cognitive Science Society (CogSci), Philadelphia, Aug 2016. - Hidden Markov Modeling of eye movements with image information lead to better discovery of regions of interest.
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In: The Annual Meeting of the Cognitive Science Society (CogSci), Philadelphia, Aug 2016. - Hidden Markov model analysis reveals better eye movement strategies in face recognition.
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In: The Annual Meeting of the Cognitive Science Society (CogSci):393-398, Pasadena, Jul 2015. - Eye Movement Pattern in Face Recognition is Associated with Cognitive Decline in the Elderly.
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In: The Annual Meeting of the Cognitive Science Society (CogSci):321-326, Pasadena, Jul 2015. - Global and Local Priming Evoke Different Face Processing Strategies: Evidence From An Eye Movement Study.
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In: Annual meeting of the Vision Sciences Society (VSS), St. Pete Beach, Florida, May 2015. - Understanding eye movements in face recognition using hidden Markov models.
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Journal of Vision, 14(11):8, Sep 2014. - Caucasian and Asian eye movement patterns in face recognition: A computational exploration using hidden Markov models.
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In: Annual meeting of the Vision Sciences Society (VSS), May 2014. - Understanding eye movements in face recognition with hidden Markov model.
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In: 6th Chinese International Conference on Eye Movements (CICEM), Beijing, May 2014 (oral). - Objective Measures of IS Usage Behavior Under Conditions of Experience and Pressure Using Eye Fixation Data.
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In: International Conference on Information Systems (ICIS), Milan, Dec 2013. - Understanding eye movements in face recognition with hidden Markov model.
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In: The Annual Meeting of the Cognitive Science Society (CogSci), Berlin, Aug 2013 (oral, Student travel award winner).
Machine Learning
- The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks.
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In: International Conference on Machine Learning (ICML), Vienna, Jul 2024. - Another Perspective of Over-Smoothing: Alleviating Semantic Over-Smoothing in Deep GNNs.
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IEEE Transactions on Neural Networks and Learning Systems (TNNLS), to appear (online May 2024). - Retrieval-Augmented Multiple Instance Learning.
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In: Neural Information Processing Systems (NeurIPS), New Orleans, Dec 2023. - Variational Nested Dropout.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 45(8):10519-10534, Aug 2023 (online Feb 2023). - TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2023. - Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios.
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Transactions on Machine Learning Research (TMLR), June 2023. - Bayes-MIL: A New Probabilistic Perspective on Attention-based Multiple Instance Learning for Whole Slide Images.
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In: Intl. Conf. on Learning Representations (ICLR), Rwanda, May 2023. - Clustering Hidden Markov Models With Variational Bayesian Hierarchical EM.
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IEEE Trans. on Neural Networks and Learning Systems (TNNLS), 34(3):1537-1551, March 2023 (online 2021). - Improved Fine-Tuning by Better Leveraging Pre-Training Data.
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In: Neural Information Processing Systems (NeurIPS), Nov 2022. - An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation.
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In: NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and Applications (DistShift), Nov 2022. - Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization.
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In: British Machine Vision Conference, Nov 2022. - Bits-Ensemble: Towards Light-Weight Robust Deep Ensemble by Bits-Sharing.
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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 41(11):4397-4408, Nov 2022 (CASES 2022). - Asymptotic Optimality for Active Learning Processes.
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In: Uncertainty in Artificial Intelligence (UAI), Aug 2022. [supplemental] - PRIMAL-GMM: PaRametrIc MAnifold Learning of Gaussian Mixture Models.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 44(6):3197-3211, June 2022 (online 2021). [code] - Accelerating Monte Carlo Bayesian Prediction via Approximating Predictive Uncertainty over the Simplex.
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IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 33(4):1492-1506, Apr 2022 (online 2020). - A Comparative Survey: Benchmarking for Pool-based Active Learning.
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In: International Joint Conf. on Artificial Intelligence (IJCAI), Survey Track, Aug 2021. - Hierarchical Learning of Hidden Markov Models with Clustering Regularization.
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In: 37th Conference on Uncertainty in Artificial Intelligence (UAI), Jul 2021. - Multiple-criteria Based Active Learning with Fixed-size Determinantal Point Processes.
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In: Subset Selection in Machine Learning: From Theory to Applications, ICML Workshop, July 2021. - Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations.
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In: ICML workshop on Adversarial Machine Learning, July 2021. - Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression.
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In: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2021. - Fully Nested Neural Network for Adaptive Compression and Quantization.
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In: International Joint Conf. on Artificial Intelligence (IJCAI), Yokohama, July 2020. [supplemental] - Parametric Manifold Learning of Gaussian Mixture Models.
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In: International Joint Conference on Artificial Intelligence (IJCAI), Macau, Aug 2019. - Density-Preserving Hierarchical EM Algorithm: Simplifying Gaussian Mixture Models for Approximate Inference.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 41(6):1323-1337, June 2019. - Learning word embeddings via context grouping.
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In: ACM Turing 50th Celebration Conference - China, Shanghai, May 2017. - Approximate Inference for Generic Likelihoods via Density-Preserving GMM Simplification.
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In: NIPS 2016 Workshop on Advances in Approximate Bayesian Inference, Barcelona, Dec 2016. - Clustering hidden Markov models with variational HEM.
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Journal of Machine Learning Research (JMLR), 15(2):697-747, Feb 2014. [code] - That was fast! Speeding up NN search of high dimensional distributions.
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In: International Conference on Machine Learning (ICML), Atlanta, Jun 2013. [supplemental | code] - The variational hierarchical EM algorithm for clustering hidden Markov models.
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In: Neural Information Processing Systems (NIPS), Lake Tahoe, Dec 2012. - Generalized Gaussian Process Models.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Colorado Springs, Jun 2011. [supplemental] - Direct Convex Relaxations of Sparse SVM.
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In: International Conference on Machine Learning (ICML), Corvallis, Jun 2007. [old version using partial wine dataset] - A Family of Probabilistic Kernels Based on Information Divergence.
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Technical Report SVCL-TR-2004-01, Jun 2004.
Data-Driven Computer Graphics
- FreeDiff: Progressive Frequency Truncation for Image Editing with Diffusion Models.
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In: European Conference on Computer Vision (ECCV), Milano, Oct 2024. - Edit Temporal-Consistent Videos with Image Diffusion Model.
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ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), to appear 2024. - System and Method for Optimizing A User Interface and A System and Method for Manipulating A User's Interaction with An Interface.
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US Patent US11275596B2, March 2022. - Angular-Driven Feedback Restoration Networks for Imperfect Sketch Recognition.
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IEEE Trans. on Image Processing (TIP), 30:5085-5095, Apr 2021. - ButtonTips: Designing Web Buttons with Suggestions.
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In: IEEE International Conference on Multimedia and Expo (ICME), Shanghai, Jul 2019. - Color Orchestra: Ordering Color Palettes for Interpolation and Prediction.
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IEEE Transactions on Visualization and Computer Graphics (TVCG), 24(6):1942-1955, June 2018. - Mining Probabilistic Color Palettes for Summarizing Color Use in Artwork Collections.
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In: Symposium on Visualization, SIGGRAPH Asia 2017, Bangkok, Nov 2017. [supplemental] - DynamicManga: Animating Still Manga via Camera Movement.
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IEEE Trans. on Multimedia (TMM), 19(1):160-172, Jan 2017. [supplemental | video] - Directing User Attention via Visual Flow on Web Designs.
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ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2016), Dec 2016. [supplemental | video] - Patternista: Learning Element Style Compatibility and Spatial Composition for Ring-based Layout Decoration.
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In: Non-Photorealistic Animation and Rendering (Expressive) 2016, Lisbon, May 2016. - FlexyFont: Learning Transferring Rules for Flexible Typeface Synthesis.
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Computer Graphics Forum (Proc. Pacific Graphics 2015), 34(7), Oct 2015. [video] - Look Over Here: Attention-Directing Composition of Manga Elements.
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ACM Transactions on Graphics (Proc. SIGGRAPH 2014), Aug 2014. [supplemental | video | slides] - Automatic Stylistic Manga Layout.
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ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2012), Singapore, Nov 2012. [supplemental | video | slides]
Human Pose Estimation
- Hand disambiguation using attention neural networks in the egocentric perspective.
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In: International Conference on Digital Image Processing (ICDIP), May 2021. - Martial Arts, Dancing and Sports Dataset: a Challenging Stereo and Multi-View Dataset for 3D Human Pose Estimation.
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Image and Vision Computing, 61:22-39, May 2017. [supplemental] - Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation.
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International Journal of Computer Vision (IJCV), 122(1):149-168, March 2017. - Maximum-Margin Structured Learning with Deep Networks for 3D Human Pose Estimation.
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In: Intl. Conf. on Computer Vision (ICCV):2848-2856, Santiago, Dec 2015. [spotlight video] - Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network.
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International Journal of Computer Vision (IJCV), 113(1):19-36, May 2015. - A Robust Likelihood Function for 3D Human Pose Tracking.
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IEEE Trans. on Image Processing (TIP), 23(12):5374-5389, Dec 2014. - 3D Human Pose Estimation from Monocular Images with Deep Convolutional Neural Network.
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In: Asian Conference on Computer Vision (ACCV), Singapore, Nov 2014. - Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network.
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In: IEEE Conf. Computer Vision and Pattern Recognition: DeepVision Workshop, Columbus, Jun 2014.
Dynamic Texture Models
- A Fully Bayesian Infinite Generative Model for Dynamic Texture Segmentation.
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arXiv:1901.03968, Jan 2019. - A Scalable and Accurate Descriptor for Dynamic Textures using Bag of System Trees.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 37(4):697-712, Apr 2015. [appendix] - Joint Motion Segmentation and Background Estimation in Dynamic Scenes.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Columbus, Jun 2014. [spotlight video] - Clustering Dynamic Textures with the Hierarchical EM Algorithm for Modeling Video.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 35(7):1606-1621, Jul 2013. [appendix] - Growing a Bag of Systems Tree for Fast and Accurate Classification.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Providence, Jun 2012. - Generalized Stauffer-Grimson background subtraction for dynamic scenes.
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Machine Vision and Applications, 22(5):751-766, Sep 2011. - Clustering Dynamic Textures with the Hierarchical EM Algorithm.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), San Francisco, Jun 2010. [supplemental] - Layered dynamic textures.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 31(10):1862-1879, Oct 2009. - Variational Layered Dynamic Textures.
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In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Miami, Jun 2009. - Derivations for the Layered Dynamic Texture and Temporally-Switching Layered Dynamic Texture.
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Technical Report SVCL-TR-2009-01, Jun 2009. - Beyond Dynamic Textures: a Family of Stochastic Dynamical Models for Video with Applications to Computer Vision.
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Ph.D. Thesis, University of California San Diego, Dec 2008. [supplemental] - Modeling, clustering, and segmenting video with mixtures of dynamic textures.
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IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 30(5):909-926, May 2008. - Classifying Video with Kernel Dynamic Textures.
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In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Minneapolis, Jun 2007. - Supplemental for "Classifying Video with Kernel Dynamic Textures".
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Technical Report SVCL-TR-2007-03, Apr 2007. [video] - Layered Dynamic Textures.
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In: Neural Information Processing Systems 18 (NIPS), Vancouver, Dec 2005. - Mixtures of Dynamic Textures.
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In: IEEE International Conference on Computer Vision (ICCV), Beijing, Oct 2005. - Classification and Retrieval of Traffic Video using Auto-regressive Stochastic Processes.
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In: 2005 IEEE Intelligent Vehicles Symposium (IEEEIV), Las Vegas, Jun 2005. - Probabilistic Kernels for the Classification of Auto-regressive Visual Processes.
,
In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), San Diego, Jun 2005. [8-page version] - The EM Algorithm for Mixtures of Dynamic Textures.
,
Technical Report SVCL-TR-2005-02, Jan 2005. [see 2008 TPAMI paper] - Efficient Computation of the KL Divergence between Dynamic Textures.
,
Technical Report SVCL-TR-2004-02, Nov 2004. [a more efficient algorithm is discussed in my thesis]
Music Analysis
- Information Distribution within Musical Segments.
,
Music Perception: An Interdisciplinary Journal, 34:218-242, Dec 2016. - A Bag of Systems Representation for Music Auto-tagging.
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IEEE Trans. on Audio, Speech and Language Processing (TASLP), 21(12):2554-2569, Dec 2013. - Multivariate autoregressive mixture models for music auto-tagging.
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In: International Society for Music Information Retrieval Conference (ISMIR), Porto, Oct 2012. - Time Series Models for Semantic Music Annotation.
,
IEEE Trans. on Audio, Speech and Language Processing (TASLP), 19(5):1343-1359, Jul 2011. - Genre Classification and the Invariance of MFCC Features to Key and Tempo.
,
In: Intl. Conference on MultiMedia Modeling (MMM), Taipei, Jan 2011. - Automatic music tagging with time series models.
,
In: International Society for Music Information Retrieval Conference (ISMIR), Utrecht, Aug 2010. - Modeling music as a dynamic texture.
,
IEEE Trans. on Audio, Speech and Language Processing (TASLP), 18(3):602-612, Mar 2010. - Automatic Musical Pattern Feature Extraction Using Convolutional Neural Network.
,
In: Intl. MultiConference of Engineers and Computer Scientists (IMECS), Hong Kong, Mar 2010. - Dynamic Texture Models of Music.
,
In: Intl. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Taipei, Apr 2009. - Audio Information Retrieval using Semantic Similarity.
,
In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Honolulu, Apr 2007.
Other Projects
- Affecting Audience Valence and Arousal in 360 Immersive Environments: How Powerful Neural Style Transfer Is?
,
In: HCI International 2024 Conference (HCII2024) - Virtual, Augmented, and Mixed Reality, Washington DC, Jun 2024. - Understanding and Fighting Scams: Media, Language, Appeals and Effects.
,
In: HCI International 2024 Conference (HCII2024) - Late Breaking Papers, Washington DC, Jun 2024. - RegGeoNet: Learning Regular Representations for Large-Scale 3D Point Clouds.
,
International Journal of Computer Vision (IJCV), 130:3100-3122, Dec 2022. - Precise Augmentation and Counting of Helicobacter Pylori in Histology Image.
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In: NeurIPS 2022 Workshop on Medical Imaging meets NeurIPS (MedNeurIPS), Nov 2022. - Chinese White Dolphin Detection in the Wild.
,
In: ACM Multimedia Asia (MMAsia), Gold Coast, Australia, Dec 2021. - Applying the Hidden Markov Model to Analyze Urban Mobility Patterns: An Interdisciplinary Approach.
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Chinese Geographical Science, 31(1):1-13, Feb 2021. - Video Desnowing and Deraining Based on Matrix Decomposition.
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In: IEEE Conf. Computer Vision and Pattern Recognition (CVPR), Honolulu, Jul 2017. - An SVD-based Multimodal Clustering Method for Social Event Detection.
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In: ICDE 2015 Workshop on Scalable Social Event Processing and Management (SSEPM), Seoul, Korea, Apr 2015. - On Measuring the Change in Size of Pulmonary Nodules.
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IEEE Transactions on Medical Imaging (TMI), 25(4):435-450, Apr 2006. - System, method and apparatus for small pulmonary nodule computer aided diagnosis from computed tomography scans.
,
US Patents 7,499,578 B2 (2009) and 7,751,607 B2 (2010).
External links: 
Google Scholar | 
Microsoft Academic | 
orcid.org/0000-0002-2886-2513 | Scopus ID: 14015159100
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