Zero-Shot Action Recognition
The zero-shot action recognition aims to recognize unseen/novel action categories by exploiting semantics and seen/known actions
State-of-the-art leaderboards
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Subtasks
Greatest papers with code
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions
CVPR 2018
• tensorflow/models
• 
The AVA dataset densely annotates 80 atomic visual actions in 430 15-minute video clips, where actions are localized in space and time, resulting in 1. 58M action labels with multiple labels per person occurring frequently.
ACTION LOCALIZATION VIDEO UNDERSTANDING ZERO-SHOT ACTION RECOGNITION
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
Dynamics of human body skeletons convey significant information for human action recognition.
#2 best model for
Skeleton Based Action Recognition
on Varying-view RGB-D Action-Skeleton
3D HUMAN POSE ESTIMATION ACTION RECOGNITION IN VIDEOS MULTIMODAL ACTIVITY RECOGNITION SKELETON BASED ACTION RECOGNITION
Temporal Segment Networks for Action Recognition in Videos
• yjxiong/temporal-segment-networks
• 
Furthermore, based on the temporal segment networks, we won the video classification track at the ActivityNet challenge 2016 among 24 teams, which demonstrates the effectiveness of TSN and the proposed good practices.
#6 best model for
Action Classification
on Moments in Time
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
• yjxiong/temporal-segment-networks
•
The other contribution is our study on a series of good practices in learning ConvNets on video data with the help of temporal segment network.
#3 best model for
Multimodal Activity Recognition
on EV-Action
ACTION RECOGNITION IN VIDEOS MULTIMODAL ACTIVITY RECOGNITION
Sparse 3D convolutional neural networks
• facebookresearch/SparseConvNet
•
We have implemented a convolutional neural network designed for processing sparse three-dimensional input data.
A Closer Look at Spatiotemporal Convolutions for Action Recognition
CVPR 2018 • facebookresearch/R2Plus1D
In this paper we discuss several forms of spatiotemporal convolutions for video analysis and study their effects on action recognition.
#2 best model for
Action Recognition In Videos
on Sports-1M
Real-time Action Recognition with Enhanced Motion Vector CNNs
The deep two-stream architecture exhibited excellent performance on video based action recognition.
Towards Good Practices for Very Deep Two-Stream ConvNets
However, for action recognition in videos, the improvement of deep convolutional networks is not so evident.
Convolutional Two-Stream Network Fusion for Video Action Recognition
CVPR 2016 • feichtenhofer/twostreamfusion
Recent applications of Convolutional Neural Networks (ConvNets) for human action recognition in videos have proposed different solutions for incorporating the appearance and motion information.
TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity Recognition
• jeffreyhuang1/two-stream-action-recognition
We demonstrate that using both RNNs (using LSTMs) and Temporal-ConvNets on spatiotemporal feature matrices are able to exploit spatiotemporal dynamics to improve the overall performance.
ACTION CLASSIFICATION ACTION RECOGNITION IN VIDEOS VIDEO UNDERSTANDING