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 926950 of 2759 papers

TitleStatusHype
Ecsnet: Spatio-temporal feature learning for event cameraCode0
Actor-identified Spatiotemporal Action Detection --- Detecting Who Is Doing What in VideosCode0
CMD: Self-supervised 3D Action Representation Learning with Cross-modal Mutual DistillationCode1
Modality Mixer for Multi-modal Action Recognition0
Lane Change Classification and Prediction with Action Recognition NetworksCode1
Hierarchically Decomposed Graph Convolutional Networks for Skeleton-Based Action RecognitionCode1
Efficient Attention-free Video Shift Transformers0
Identifying Auxiliary or Adversarial Tasks Using Necessary Condition Analysis for Adversarial Multi-task Video Understanding0
Review on Action Recognition for Accident Detection in Smart City Transportation Systems0
Net2Brain: A Toolbox to compare artificial vision models with human brain responsesCode1
Part-aware Prototypical Graph Network for One-shot Skeleton-based Action Recognition0
Hierarchical Compositional Representations for Few-shot Action Recognition0
Synthetic Data in Human Analysis: A Survey0
Spatial Temporal Graph Attention Network for Skeleton-Based Action RecognitionCode1
Progressive Cross-modal Knowledge Distillation for Human Action Recognition0
Unsupervised Video Domain Adaptation for Action Recognition: A Disentanglement PerspectiveCode1
Action Recognition based on Cross-Situational Action-object StatisticsCode0
Two-person Graph Convolutional Network for Skeleton-based Human Interaction RecognitionCode0
PSUMNet: Unified Modality Part Streams are All You Need for Efficient Pose-based Action RecognitionCode1
Leveraging Endo- and Exo-Temporal Regularization for Black-box Video Domain Adaptation0
Generative Action Description Prompts for Skeleton-based Action RecognitionCode1
Spatial-Temporal Pyramid Graph Reasoning for Action Recognition0
Sports Video Analysis on Large-Scale DataCode1
BabyNet: A Lightweight Network for Infant Reaching Action Recognition in Unconstrained Environments to Support Future Pediatric Rehabilitation Applications0
Human Activity Recognition Using Cascaded Dual Attention CNN and Bi-Directional GRU Framework0
Show:102550
← PrevPage 38 of 111Next →

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