Downloads

Video Datasets

Experimental setup for semantic video texture annotation on the DynTex dataset

Videos can be obtained from the DynTex website.  The text files contain the list of selected tags, the list of selected videos and ground-truth tags, and the training/test set splits.

Boats Videos

A video of boats moving through water.  A challenging background subtraction task, where the background itself is moving.

boatseg

Synthetic Video Texture Dataset

A dataset of composite video textures.  The videos were created by compositing different video textures together into a template with 2, 3, or 4 segments.

synthdb_eg

Highway Traffic Dataset (Clustering)

A dataset of highway traffic videos used for clustering video textures.

traffic_eg_sm

Highway Traffic Videos (Classification)

A set of highway traffic videos. Each video is classified as low, medium, or high traffic.

traffic_eg_sm_class

Crowd Datasets

UCSD Pedestrian Dataset

Video of people on pedestrian walkways at UCSD, and the corresponding motion segmentations. Currently two scenes are available.

ucsdpeds-vids

People Annotations for UCSD Dataset

People annotations, perspective density maps, region-of-interest, and crowd counts for the UCSD Pedestrian Dataset.ucsdpeds-gt-sm

People Counting Data for UCSD Dataset

The features and counts for people counting on the UCSD Dataset. This data should be sufficient if you are interested in the regression problem only. Includes the Peds1, Peds2, and CVPR counting datasets.

People Counting Data for PETS2009 Dataset

The features and counts for people counting on the PETS2009 Dataset.  Also includes the segmentations, perspective maps, and ground-truth annotations.

Line Counting Dataset

These are the ground-truth annotations for line counting on the UCSD, Grand Central, and LHI datasets.

linecount

Human Pose Datasets

MADS: Martial Arts, Dancing, and Sports Dataset

A multi-view and stereo-depth dataset for 3D human pose estimation, which consists of challenging martial arts actions (Tai-chi and Karate), dancing actions (hip-hop and jazz), and sports actions (basketball, volleyball, football, rugby, tennis and badminton).

mads-featured

 

Other Datasets

Small Object Dataset

Images of small objects for small instance detections.  Currently four object types are available.

smallobject

Manga Layout Dataset

Dataset of manga panel layouts.

data_thumbnail

  • Files: zip
  • If you use this dataset please cite:
    Automatic Stylistic Manga Layout.
    Ying Cao, Antoni B. Chan, and Rynson W.H. Lau,
    ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2012), Singapore, Nov 2012.
Key annotations for the GTZAN music genre dataset

Ground-truth annotations of the musical keys of songs in the GTZAN music genre dataset.

Code

Eye Movement Hidden Markov Models (EMHMM) Toolbox

This is a MATLAB toolbox for analyzing eye movement data using hidden Markov models. It includes code for learning HMMs for individuals, as well as clustering indivduals’ HMMs into groups.

fixeg

Manga panel extraction toolbox

This is a MATLAB toolbox for automatically extracting the panels from digital manga/comic pages.

VarBB Toolbox

The VarBB toolbox is an implementation for the variational branch-and-bound algorithm for Bregman ball trees (bb-trees).  VarBB can speed up nearest neighbor search for generative models.

H3M toolbox

This is a MATLAB toolbox for clustering hidden Markov models using the variational HEM algorithm.  The toolbox can also estimate HMM mixtures (H3M) using the EM algorithm.

libdt – OpenCV library for Dynamic Textures

This is an OpenCV C++ library for Dynamic Teture (DT) models.  It contains code for the EM algorithm for learning DTs and DT mixture models, and the HEM algorithm for clustering DTs, as well as DT-based applications, such as motion segmentation and Bag-of-Systems (BoS) motion descriptors.

Generalized Gaussian Process Models Toolbox

This is a toolbox for generalized Gaussian process models (GGPM). The toolbox is implemented as an add-on to the GPML toolbox for Matlab/Octave. The toolbox contains likelihood functions for GGPMs, as well as a Taylor inference function. GPML version 3.4 is supported.