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 23762400 of 2759 papers

TitleStatusHype
Nested Grassmannians for Dimensionality Reduction with ApplicationsCode0
Memory Attention Networks for Skeleton-based Action RecognitionCode0
Skeleton-based Action Recognition via Adaptive Cross-Form LearningCode0
MD-BERT: Action Recognition in Dark Videos via Dynamic Multi-Stream Fusion and Temporal ModelingCode0
Tensor Analysis with n-Mode Generalized Difference SubspaceCode0
NEV-NCD: Negative Learning, Entropy, and Variance regularization based novel action categories discoveryCode0
Conditional Extreme Value Theory for Open Set Video Domain AdaptationCode0
Mask and Compress: Efficient Skeleton-based Action Recognition in Continual LearningCode0
First and Second Order Dynamics in a Hierarchical SOM system for Action RecognitionCode0
Skeleton-Based Action Recognition with Spatial-Structural Graph ConvolutionCode0
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
Non-Local Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
MARS: Motion-Augmented RGB Stream for Action RecognitionCode0
Skeleton-Based Action Recognition With Directed Graph Neural NetworksCode0
MARINE: A Computer Vision Model for Detecting Rare Predator-Prey Interactions in Animal VideosCode0
Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional NetworksCode0
Skeleton-based Action Recognition with Non-linear Dependency Modeling and Hilbert-Schmidt Independence CriterionCode0
Fine-grained Affordance Annotation for Egocentric Hand-Object Interaction VideosCode0
Mamba Fusion: Learning Actions Through QuestioningCode0
Making Third Person Techniques Recognize First-Person Actions in Egocentric VideosCode0
NTU RGB+D: A Large Scale Dataset for 3D Human Activity AnalysisCode0
ActivityNet: A Large-Scale Video Benchmark for Human Activity UnderstandingCode0
Actions ~ TransformationsCode0
A Recurrent Transformer Network for Novel View Action SynthesisCode0
Skeleton-Based Human Action Recognition with Noisy LabelsCode0
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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