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 301325 of 2759 papers

TitleStatusHype
CMD: Self-supervised 3D Action Representation Learning with Cross-modal Mutual DistillationCode1
HierVL: Learning Hierarchical Video-Language EmbeddingsCode1
BABEL: Bodies, Action and Behavior with English LabelsCode1
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video DatasetCode1
ViNet: Pushing the limits of Visual Modality for Audio-Visual Saliency PredictionCode1
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
Complex Sequential Understanding through the Awareness of Spatial and Temporal ConceptsCode1
Compressing Recurrent Neural Networks with Tensor Ring for Action RecognitionCode1
Actor-Context-Actor Relation Network for Spatio-Temporal Action LocalizationCode1
Hypergraph Transformer for Skeleton-based Action RecognitionCode1
Action-Conditioned 3D Human Motion Synthesis with Transformer VAECode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
Volterra Neural Networks (VNNs)Code1
MViTv2: Improved Multiscale Vision Transformers for Classification and DetectionCode1
IndustReal: A Dataset for Procedure Step Recognition Handling Execution Errors in Egocentric Videos in an Industrial-Like SettingCode1
Conquering the cnn over-parameterization dilemma: A volterra filtering approach for action recognitionCode1
Constructing Stronger and Faster Baselines for Skeleton-based Action RecognitionCode1
Context-Aware RCNN: A Baseline for Action Detection in VideosCode1
AViD Dataset: Anonymized Videos from Diverse CountriesCode1
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual ActionsCode1
FreqMixFormerV2: Lightweight Frequency-aware Mixed Transformer for Human Skeleton Action RecognitionCode1
Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action RecognitionCode1
Anonymization for Skeleton Action RecognitionCode1
Counterfactual Debiasing Inference for Compositional Action RecognitionCode1
AutoLabel: CLIP-based framework for Open-set Video Domain AdaptationCode1
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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
4InternVideoTop-1 Accuracy77.2Unverified
5DejaVidTop-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
3OmniVec3-fold Accuracy99.6Unverified
4VideoMAE V2-g3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
10Text4Vis3-fold Accuracy98.2Unverified