SOTAVerified

Action Recognition

Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.

In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.

Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.

Papers

Showing 22262250 of 2759 papers

TitleStatusHype
Videos as Space-Time Region Graphs0
Squeeze-and-Excitation on Spatial and Temporal Deep Feature Space for Action Recognition0
Temporal Hallucinating for Action Recognition With Few Still Images0
Pulling Actions out of Context: Explicit Separation for Effective Combination0
Learning and Using the Arrow of Time0
SSNet: Scale Selection Network for Online 3D Action Prediction0
PoTion: Pose MoTion Representation for Action Recognition0
Recognize Actions by Disentangling Components of Dynamics0
Coding Kendall's Shape Trajectories for 3D Action Recognition0
PoseFlow: A Deep Motion Representation for Understanding Human Behaviors in Videos0
Recognizing Human Actions as the Evolution of Pose Estimation Maps0
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning0
Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition0
Making Convolutional Networks Recurrent for Visual Sequence Learning0
MiCT: Mixed 3D/2D Convolutional Tube for Human Action Recognition0
RNN for Affects at SemEval-2018 Task 1: Formulating Affect Identification as a Binary Classification Problem0
A Fine-to-Coarse Convolutional Neural Network for 3D Human Action Recognition0
Pose-Based Two-Stream Relational Networks for Action Recognition in Videos0
DEEPEYE: A Compact and Accurate Video Comprehension at Terminal Devices Compressed with Quantization and Tensorization0
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning0
Graph Edge Convolutional Neural Networks for Skeleton Based Action Recognition0
Towards an Unequivocal Representation of Actions0
Visual Attribute-augmented Three-dimensional Convolutional Neural Network for Enhanced Human Action Recognition0
Low-Latency Human Action Recognition with Weighted Multi-Region Convolutional Neural Network0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MViTv2-B (IN-21K + Kinetics400 pretrain)Top-5 Accuracy93.4Unverified
2RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)Top-5 Accuracy91.1Unverified
3MVD (Kinetics400 pretrain, ViT-H, 16 frame)Top-1 Accuracy77.3Unverified
4DejaVidTop-1 Accuracy77.2Unverified
5InternVideoTop-1 Accuracy77.2Unverified
6InternVideo2-1BTop-1 Accuracy77.1Unverified
7VideoMAE V2-gTop-1 Accuracy77Unverified
8MVD (Kinetics400 pretrain, ViT-L, 16 frame)Top-1 Accuracy76.7Unverified
9Hiera-L (no extra data)Top-1 Accuracy76.5Unverified
10TubeViT-LTop-1 Accuracy76.1Unverified
#ModelMetricClaimedVerifiedStatus
1FTP-UniFormerV2-L/143-fold Accuracy99.7Unverified
2OmniVec23-fold Accuracy99.6Unverified
3VideoMAE V2-g3-fold Accuracy99.6Unverified
4OmniVec3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
9ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
10LGD-3D Two-stream3-fold Accuracy98.2Unverified