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 251300 of 2759 papers

TitleStatusHype
Sports Video Analysis on Large-Scale DataCode1
Privacy-Preserving Action Recognition via Motion Difference QuantizationCode1
Spatiotemporal Self-attention Modeling with Temporal Patch Shift for Action RecognitionCode1
SSIVD-Net: A Novel Salient Super Image Classification & Detection Technique for Weaponized ViolenceCode1
MAR: Masked Autoencoders for Efficient Action RecognitionCode1
Discover and Mitigate Unknown Biases with Debiasing Alternate NetworksCode1
Collaborating Domain-shared and Target-specific Feature Clustering for Cross-domain 3D Action RecognitionCode1
Hierarchically Self-Supervised Transformer for Human Skeleton Representation LearningCode1
Task-adaptive Spatial-Temporal Video Sampler for Few-shot Action RecognitionCode1
Time Is MattEr: Temporal Self-supervision for Video TransformersCode1
Is Appearance Free Action Recognition Possible?Code1
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action RecognitionCode1
Federated Self-supervised Learning for Video UnderstandingCode1
Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action RecognitionCode1
ST-Adapter: Parameter-Efficient Image-to-Video Transfer LearningCode1
Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D SpaceCode1
Stand-Alone Inter-Frame Attention in Video ModelsCode1
A Deeper Dive Into What Deep Spatiotemporal Networks Encode: Quantifying Static vs. Dynamic InformationCode1
Stargazer: A transformer-based driver action detection system for intelligent transportationCode1
Skeleton-based Action Recognition via Temporal-Channel AggregationCode1
PSTNet: Point Spatio-Temporal Convolution on Point Cloud SequencesCode1
Cross-Architecture Self-supervised Video Representation LearningCode1
MMNet: A Model-Based Multimodal Network for Human Action Recognition in RGB-D VideosCode1
TransRank: Self-supervised Video Representation Learning via Ranking-based Transformation RecognitionCode1
Hybrid Relation Guided Set Matching for Few-shot Action RecognitionCode1
MILES: Visual BERT Pre-training with Injected Language Semantics for Video-text RetrievalCode1
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior UnderstandingCode1
Temporal Alignment Networks for Long-term VideoCode1
TALLFormer: Temporal Action Localization with a Long-memory TransformerCode1
Stochastic Backpropagation: A Memory Efficient Strategy for Training Video ModelsCode1
SPAct: Self-supervised Privacy Preservation for Action RecognitionCode1
Continual Spatio-Temporal Graph Convolutional NetworksCode1
DirecFormer: A Directed Attention in Transformer Approach to Robust Action RecognitionCode1
Group Contextualization for Video RecognitionCode1
Source-free Video Domain Adaptation by Learning Temporal Consistency for Action RecognitionCode1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
Motion-driven Visual Tempo Learning for Video-based Action RecognitionCode1
Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse OcclusionsCode1
Student Dangerous Behavior Detection in SchoolCode1
Source-Free Progressive Graph Learning for Open-Set Domain AdaptationCode1
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensorsCode1
MeMViT: Memory-Augmented Multiscale Vision Transformer for Efficient Long-Term Video RecognitionCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
TSA-Net: Tube Self-Attention Network for Action Quality AssessmentCode1
Spatio-Temporal Tuples Transformer for Skeleton-Based Action RecognitionCode1
E2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action RecognitionCode1
InfoGCN: Representation Learning for Human Skeleton-Based Action RecognitionCode1
Tell me what you see: A zero-shot action recognition method based on natural language descriptionsCode1
Masked Feature Prediction for Self-Supervised Visual Pre-TrainingCode1
SVIP: Sequence VerIfication for Procedures in VideosCode1
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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