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 826850 of 2759 papers

TitleStatusHype
PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data0
Masked Video Distillation: Rethinking Masked Feature Modeling for Self-supervised Video Representation LearningCode1
Learning Video Representations from Large Language ModelsCode2
Rethinking Video ViTs: Sparse Video Tubes for Joint Image and Video LearningCode1
InternVideo: General Video Foundation Models via Generative and Discriminative LearningCode4
Hierarchical Contrast for Unsupervised Skeleton-based Action Representation LearningCode1
ResFormer: Scaling ViTs with Multi-Resolution TrainingCode1
From Actions to Events: A Transfer Learning Approach Using Improved Deep Belief Networks0
Towards Good Practices for Missing Modality Robust Action RecognitionCode1
Video Test-Time Adaptation for Action RecognitionCode1
Hierarchical Consistent Contrastive Learning for Skeleton-Based Action Recognition with Growing AugmentationsCode1
Hand Guided High Resolution Feature Enhancement for Fine-Grained Atomic Action Segmentation within Complex Human Assemblies0
Global Temporal Difference Network for Action Recognition0
Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition0
Mitigating and Evaluating Static Bias of Action Representations in the Background and the ForegroundCode1
Dynamic Appearance: A Video Representation for Action Recognition with Joint Training0
SVFormer: Semi-supervised Video Transformer for Action RecognitionCode1
Knowledge Prompting for Few-shot Action Recognition0
Event Transformer+. A multi-purpose solution for efficient event data processing0
EVEREST: Efficient Masked Video Autoencoder by Removing Redundant Spatiotemporal TokensCode1
Look More but Care Less in Video RecognitionCode1
3d human motion generation from the text via gesture action classification and the autoregressive model0
Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive SurveyCode1
Language-Assisted Deep Learning for Autistic Behaviors Recognition0
Hypergraph Transformer for Skeleton-based Action RecognitionCode1
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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