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Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

CVPR 2017 deepmind/kinetics-i3d

The paucity of videos in current action classification datasets (UCF-101 and HMDB-51) has made it difficult to identify good video architectures, as most methods obtain similar performance on existing small-scale benchmarks.

#3 best model for Action Classification on HMDB51 (using extra training data)

ACTION RECOGNITION IN VIDEOS SKELETON BASED ACTION RECOGNITION

Graph Attention Networks

ICLR 2018 PetarV-/GAT

We present graph attention networks (GATs), novel neural network architectures that operate on graph-structured data, leveraging masked self-attentional layers to address the shortcomings of prior methods based on graph convolutions or their approximations.

DOCUMENT CLASSIFICATION GRAPH EMBEDDING GRAPH REGRESSION LINK PREDICTION NODE CLASSIFICATION SKELETON BASED ACTION RECOGNITION

Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNN

CVPR 2018 TobiasLee/Text-Classification

Experimental results have shown that the proposed IndRNN is able to process very long sequences (over 5000 time steps), can be used to construct very deep networks (21 layers used in the experiment) and still be trained robustly.

SKELETON BASED ACTION RECOGNITION

Temporal Convolutional Networks for Action Segmentation and Detection

CVPR 2017 coderSkyChen/Action_Recognition_Zoo

The ability to identify and temporally segment fine-grained human actions throughout a video is crucial for robotics, surveillance, education, and beyond.

SKELETON BASED ACTION RECOGNITION

Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation

17 Apr 2018huguyuehuhu/HCN-pytorch

Skeleton-based human action recognition has recently drawn increasing attentions with the availability of large-scale skeleton datasets.

SKELETON BASED ACTION RECOGNITION

Non-Local Graph Convolutional Networks for Skeleton-Based Action Recognition

arXiv 2019 lshiwjx/2s-AGCN

However, the topology of the graph is set by hand and fixed over all layers, which may be not optimal for the action recognition task and the hierarchical CNN structures.

SKELETON BASED ACTION RECOGNITION

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

CVPR 2019 lshiwjx/2s-AGCN

In addition, the second-order information (the lengths and directions of bones) of the skeleton data, which is naturally more informative and discriminative for action recognition, is rarely investigated in existing methods.

GRAPH CONSTRUCTION SKELETON BASED ACTION RECOGNITION