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 51100 of 2759 papers

TitleStatusHype
EgoVideo: Exploring Egocentric Foundation Model and Downstream AdaptationCode2
Omnivore: A Single Model for Many Visual ModalitiesCode2
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and TransportationCode2
Omni-sourced Webly-supervised Learning for Video RecognitionCode2
Dynamic 3D Point Cloud Sequences as 2D VideosCode2
Deep Architectures for Content Moderation and Movie Content RatingCode2
BlockGCN: Redefine Topology Awareness for Skeleton-Based Action RecognitionCode2
DeGCN: Deformable Graph Convolutional Networks for Skeleton-Based Action RecognitionCode2
Egocentric Video-Language PretrainingCode2
Hierarchical NeuroSymbolic Approach for Comprehensive and Explainable Action Quality AssessmentCode2
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action RecognitionCode1
ConvNet Architecture Search for Spatiotemporal Feature LearningCode1
3D Human Action Representation Learning via Cross-View Consistency PursuitCode1
A Comprehensive Study of Deep Video Action RecognitionCode1
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action RecognitionCode1
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
ARID: A New Dataset for Recognizing Action in the DarkCode1
AR-Net: Adaptive Frame Resolution for Efficient Action RecognitionCode1
Constructing Stronger and Faster Baselines for Skeleton-based Action RecognitionCode1
ArtEmis: Affective Language for Visual ArtCode1
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the WildCode1
Conquering the cnn over-parameterization dilemma: A volterra filtering approach for action recognitionCode1
Context-Aware RCNN: A Baseline for Action Detection in VideosCode1
Counterfactual Debiasing Inference for Compositional Action RecognitionCode1
A Closer Look at Spatiotemporal Convolutions for Action RecognitionCode1
Compressing Recurrent Neural Networks with Tensor Ring for Action RecognitionCode1
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video DatasetCode1
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior UnderstandingCode1
Anonymization for Skeleton Action RecognitionCode1
Complex Sequential Understanding through the Awareness of Spatial and Temporal ConceptsCode1
Concatenated Masked Autoencoders as Spatial-Temporal LearnerCode1
A Body Part Embedding Model With Datasets for Measuring 2D Human Motion SimilarityCode1
CoCon: Cooperative-Contrastive LearningCode1
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction AlignmentCode1
CLIP-guided Prototype Modulating for Few-shot Action RecognitionCode1
An Image is Worth 16x16 Words, What is a Video Worth?Code1
CMD: Self-supervised 3D Action Representation Learning with Cross-modal Mutual DistillationCode1
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
Volterra Neural Networks (VNNs)Code1
Cross-Architecture Self-supervised Video Representation LearningCode1
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
ACTION-Net: Multipath Excitation for Action RecognitionCode1
Full-Body Articulated Human-Object InteractionCode1
A Lie Group Approach to Riemannian Batch NormalizationCode1
3D CNNs with Adaptive Temporal Feature ResolutionsCode1
An Evaluation of Action Recognition Models on EPIC-KitchensCode1
Approximated Bilinear Modules for Temporal ModelingCode1
CIDEr: Consensus-based Image Description EvaluationCode1
Can An Image Classifier Suffice For Action Recognition?Code1
A Local-to-Global Approach to Multi-modal Movie Scene SegmentationCode1
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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
2OmniVec3-fold Accuracy99.6Unverified
3VideoMAE V2-g3-fold Accuracy99.6Unverified
4OmniVec23-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
9OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
10Text4Vis3-fold Accuracy98.2Unverified