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 101150 of 2759 papers

TitleStatusHype
A Body Part Embedding Model With Datasets for Measuring 2D Human Motion SimilarityCode1
AutoLabel: CLIP-based framework for Open-set Video Domain AdaptationCode1
AViD Dataset: Anonymized Videos from Diverse CountriesCode1
Deep Analysis of CNN-based Spatio-temporal Representations for Action RecognitionCode1
Deep Multimodal Feature Encoding for Video OrderingCode1
Dual-path Adaptation from Image to Video TransformersCode1
B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action RecognitionCode1
BackdoorMBTI: A Backdoor Learning Multimodal Benchmark Tool Kit for Backdoor Defense EvaluationCode1
A Closer Look at Spatiotemporal Convolutions for Action RecognitionCode1
BABEL: Bodies, Action and Behavior with English LabelsCode1
BMN: Boundary-Matching Network for Temporal Action Proposal GenerationCode1
BASAR:Black-box Attack on Skeletal Action RecognitionCode1
Benchmarking Micro-action Recognition: Dataset, Methods, and ApplicationsCode1
Action knowledge for video captioning with graph neural networksCode1
Attention Prompt Tuning: Parameter-efficient Adaptation of Pre-trained Models for Spatiotemporal ModelingCode1
DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 PandemicCode1
Blindly Assess Quality of In-the-Wild Videos via Quality-aware Pre-training and Motion PerceptionCode1
Disentangled Non-Local Neural NetworksCode1
AR-Net: Adaptive Frame Resolution for Efficient Action RecognitionCode1
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action RecognitionCode1
3D Human Action Representation Learning via Cross-View Consistency PursuitCode1
EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the BackboneCode1
Bridging Video-text Retrieval with Multiple Choice QuestionsCode1
Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and DataCode1
Bringing Online Egocentric Action Recognition into the wildCode1
BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket SportsCode1
ARID: A New Dataset for Recognizing Action in the DarkCode1
ArtEmis: Affective Language for Visual ArtCode1
Data Efficient Video Transformer for Violence DetectionCode1
3DYoga90: A Hierarchical Video Dataset for Yoga Pose UnderstandingCode1
DDGCN: A Dynamic Directed Graph Convolutional Network for Action RecognitionCode1
Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action RecognitionCode1
Action Genome: Actions as Composition of Spatio-temporal Scene GraphsCode1
3DV: 3D Dynamic Voxel for Action Recognition in Depth VideoCode1
ARBEE: Towards Automated Recognition of Bodily Expression of Emotion In the WildCode1
Approximated Bilinear Modules for Temporal ModelingCode1
D^2ST-Adapter: Disentangled-and-Deformable Spatio-Temporal Adapter for Few-shot Action RecognitionCode1
DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action RecognitionCode1
Decoupling GCN with DropGraph Module for Skeleton-Based Action RecognitionCode1
Disentangled Pre-training for Human-Object Interaction DetectionCode1
Can An Image Classifier Suffice For Action Recognition?Code1
Action-Conditioned 3D Human Motion Synthesis with Transformer VAECode1
An Image is Worth 16x16 Words, What is a Video Worth?Code1
An Evaluation of Action Recognition Models on EPIC-KitchensCode1
Animal Kingdom: A Large and Diverse Dataset for Animal Behavior UnderstandingCode1
Counterfactual Debiasing Inference for Compositional Action RecognitionCode1
Cross-Architecture Self-supervised Video Representation LearningCode1
ActionCLIP: A New Paradigm for Video Action RecognitionCode1
Contrastive Learning from Spatio-Temporal Mixed Skeleton Sequences for Self-Supervised Skeleton-Based Action RecognitionCode1
Context-Aware RCNN: A Baseline for Action Detection 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
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