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 13761400 of 2759 papers

TitleStatusHype
Skeleton-Based Human Action Recognition with Global Context-Aware Attention LSTM Networks0
Skeleton-Based Mutually Assisted Interacted Object Localization and Human Action Recognition0
Relational Network for Skeleton-Based Action Recognition0
Skeleton based Zero Shot Action Recognition in Joint Pose-Language Semantic Space0
Skeleton Boxes: Solving skeleton based action detection with a single deep convolutional neural network0
Skeleton Cloud Colorization for Unsupervised 3D Action Representation Learning0
SkeletonMAE: Spatial-Temporal Masked Autoencoders for Self-supervised Skeleton Action Recognition0
Skeletonnet: Mining deep part features for 3-d action recognition0
Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition0
SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models0
SkeleTR: Towards Skeleton-based Action Recognition in the Wild0
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild0
SkelMamba: A State Space Model for Efficient Skeleton Action Recognition of Neurological Disorders0
Skepxels: Spatio-temporal Image Representation of Human Skeleton Joints for Action Recognition0
Skimming and Scanning for Untrimmed Video Action Recognition0
Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking0
Sliding Dictionary Based Sparse Representation For Action Recognition0
Slow and steady feature analysis: higher order temporal coherence in video0
Slow Feature Analysis for Human Action Recognition0
SMAM: Self and Mutual Adaptive Matching for Skeleton-Based Few-Shot Action Recognition0
SMART Frame Selection for Action Recognition0
SMART: Skeletal Motion Action Recognition aTtack0
SMART-Vision: Survey of Modern Action Recognition Techniques in Vision0
Smoothed Gaussian Mixture Models for Video Classification and Recommendation0
SNN-Driven Multimodal Human Action Recognition via Event Camera and Skeleton Data Fusion0
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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
4DejaVidTop-1 Accuracy77.2Unverified
5InternVideoTop-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
3VideoMAE V2-g3-fold Accuracy99.6Unverified
4OmniVec3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
9ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
10LGD-3D Two-stream3-fold Accuracy98.2Unverified