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 451500 of 2759 papers

TitleStatusHype
DDGCN: A Dynamic Directed Graph Convolutional Network for Action RecognitionCode1
Siformer: Feature-isolated Transformer for Efficient Skeleton-based Sign Language RecognitionCode1
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
Sign Language Recognition via Skeleton-Aware Multi-Model EnsembleCode1
Skeleton-based Action Recognition via Temporal-Channel AggregationCode1
Full-Body Articulated Human-Object InteractionCode1
An Action Is Worth Multiple Words: Handling Ambiguity in Action RecognitionCode1
Challenges in Video-Based Infant Action Recognition: A Critical Examination of the State of the ArtCode1
Skeleton-DML: Deep Metric Learning for Skeleton-Based One-Shot Action RecognitionCode1
SkeletonMAE: Graph-based Masked Autoencoder for Skeleton Sequence Pre-trainingCode1
SlowFast Networks for Video RecognitionCode1
Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action RecognitionCode1
Data Efficient Video Transformer for Violence DetectionCode1
Space-time Mixing Attention for Video TransformerCode1
Sparse Adversarial Perturbations for VideosCode1
CIAGAN: Conditional Identity Anonymization Generative Adversarial NetworksCode1
CIDEr: Consensus-based Image Description EvaluationCode1
Skeleton-based Action Recognition via Spatial and Temporal Transformer NetworksCode1
Spatiotemporal Contrastive Video Representation LearningCode1
Spatio-Temporal Inception Graph Convolutional Networks for Skeleton-Based Action RecognitionCode1
Spatiotemporal Self-attention Modeling with Temporal Patch Shift for Action RecognitionCode1
Spatio-Temporal Tuples Transformer for Skeleton-Based Action RecognitionCode1
SpikMamba: When SNN meets Mamba in Event-based Human Action RecognitionCode1
Sports Video Analysis on Large-Scale DataCode1
CLIP-guided Prototype Modulating for Few-shot Action RecognitionCode1
STAR: Sparse Transformer-based Action RecognitionCode1
STMT: A Spatial-Temporal Mesh Transformer for MoCap-Based Action RecognitionCode1
Stochastic Backpropagation: A Memory Efficient Strategy for Training Video ModelsCode1
CMD: Self-supervised 3D Action Representation Learning with Cross-modal Mutual DistillationCode1
A Comprehensive Study of Deep Video Action RecognitionCode1
SVIP: Sequence VerIfication for Procedures in VideosCode1
Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action RecognitionCode1
CT-Net: Channel Tensorization Network for Video ClassificationCode1
CoCon: Cooperative-Contrastive LearningCode1
TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action RecognitionCode1
CoFInAl: Enhancing Action Quality Assessment with Coarse-to-Fine Instruction AlignmentCode1
3D Human Action Representation Learning via Cross-View Consistency PursuitCode1
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
TCLR: Temporal Contrastive Learning for Video RepresentationCode1
TDN: Temporal Difference Networks for Efficient Action RecognitionCode1
TEA: Temporal Excitation and Aggregation for Action RecognitionCode1
Technical Report: Temporal Aggregate RepresentationsCode1
Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action RecognitionCode1
Temporal 3D ConvNets: New Architecture and Transfer Learning for Video ClassificationCode1
DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action RecognitionCode1
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence ClassificationCode1
An Evaluation of Action Recognition Models on EPIC-KitchensCode1
Temporally Guided Articulated Hand Pose Tracking in Surgical VideosCode1
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior UnderstandingCode1
An Image is Worth 16x16 Words, What is a Video Worth?Code1
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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