PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.

Efficient 3D human pose estimation in video using 2D keypoint trajectories

A deep learning library for video understanding research.

State-of-the-art Image & Video CLIP, Multimodal Large Language Models, and More!

Fully Convolutional Instance-aware Semantic Segmentation

Hiera: A fast, powerful, and simple hierarchical vision transformer.

Code release for "Convolutional Two-Stream Network Fusion for Video Action Recognition", CVPR 2016.

Macro to draw architecture of convolutional neural nets in tikz.

Sublinear memory optimization for deep learning, reduce GPU memory cost to train deeper nets

Code release for "Spatiotemporal Residual Networks for Video Action Recognition", NIPS16 & "Spatiotemporal Multiplier Networks for Video Action Recognition", CVPR17.

Code for Visualizing Deep Convolutional Neural Networks Using Natural Pre-images, IJCV 2016