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 251275 of 2759 papers

TitleStatusHype
Decoupled Prompt-Adapter Tuning for Continual Activity Recognition0
Can VLMs be used on videos for action recognition? LLMs are Visual Reasoning Coordinators0
LORTSAR: Low-Rank Transformer for Skeleton-based Action Recognition0
Pose-guided multi-task video transformer for driver action recognition0
QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person ViewCode0
SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational AutoencodersCode1
Frequency Guidance Matters: Skeletal Action Recognition by Frequency-Aware Mixed TransformerCode1
Shap-Mix: Shapley Value Guided Mixing for Long-Tailed Skeleton Based Action RecognitionCode1
Enhancing Split Computing and Early Exit Applications through Predefined SparsityCode0
Human-Centric Transformer for Domain Adaptive Action Recognition0
STARS: Self-supervised Tuning for 3D Action Recognition in Skeleton SequencesCode1
Augmented Neural Fine-Tuning for Efficient Backdoor PurificationCode1
Region-aware Image-based Human Action Retrieval with Transformers0
Boosting Adversarial Transferability for Skeleton-based Action Recognition via Exploring the Model Posterior Space0
EA-VTR: Event-Aware Video-Text Retrieval0
Rethinking Image-to-Video Adaptation: An Object-centric Perspective0
Masked Video and Body-worn IMU Autoencoder for Egocentric Action Recognition0
DMSD-CDFSAR: Distillation from Mixed-Source Domain for Cross-Domain Few-shot Action Recognition0
C2C: Component-to-Composition Learning for Zero-Shot Compositional Action RecognitionCode1
DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action RecognitionCode1
Computer Vision for Clinical Gait Analysis: A Gait Abnormality Video DatasetCode1
AWT: Transferring Vision-Language Models via Augmentation, Weighting, and TransportationCode2
Motion meets Attention: Video Motion PromptsCode1
Advancing Compressed Video Action Recognition through Progressive Knowledge DistillationCode0
Referring Atomic Video Action RecognitionCode1
Show:102550
← PrevPage 11 of 111Next →

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