DG-Net: PyTorch implementation of joint discriminative and generative learning for person re-id.

AD: Python implementation of a delay metric to measure video object detection delay.

PWC-Net: PyTorch and Caffe implementation of accurate and fast optical flow.

MoCoGAN: PyTorch implementation for motion and content decomposed video generation.

SNV: C++/Matlab implementation of super normal vector for activity recognition.

SSCV: Matlab implementation of super sparse coding vector for action recognition.

CascadeSVMs: C++ implementation of an algorithm to handle highly imbalanced large-scale data learning.

ActionHOG: C++ implementation of an efficient local spatio-temporal feature for activity recognition.

DMM-HOG: Matlab implementation of depth motion maps for action and gesture recognition.


CityFlow is a city-scale benchmark for multi-target multi-camera vehicle tracking and re-identification.

SynHead is a large-scale synthetic dataset for video-based head pose estimation.

NVGesture is a multi-modal (color, depth, optical flow and stereo-IR) dataset for online detection and classification of dynamic hand gestures.