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 15261550 of 2759 papers

TitleStatusHype
DIY Human Action Data Set Generation0
DL-KDD: Dual-Light Knowledge Distillation for Action Recognition in the Dark0
DL-SFA: Deeply-Learned Slow Feature Analysis for Action Recognition0
DMC-Net: Generating Discriminative Motion Cues for Fast Compressed Video Action Recognition0
DMMG: Dual Min-Max Games for Self-Supervised Skeleton-Based Action Recognition0
DMSD-CDFSAR: Distillation from Mixed-Source Domain for Cross-Domain Few-shot Action Recognition0
DOAD: Decoupled One Stage Action Detection Network0
Do Less and Achieve More: Training CNNs for Action Recognition Utilizing Action Images from the Web0
Domain Generalization: A Survey0
Domain Generalization through Audio-Visual Relative Norm Alignment in First Person Action Recognition0
Domain-Specific Priors and Meta Learning for Few-Shot First-Person Action Recognition0
Dominant Codewords Selection with Topic Model for Action Recognition0
Down-Sampling coupled to Elastic Kernel Machines for Efficient Recognition of Isolated Gestures0
Drive&Act: A Multi-Modal Dataset for Fine-Grained Driver Behavior Recognition in Autonomous Vehicles0
Driver Activity Classification Using Generalizable Representations from Vision-Language Models0
DTG-Net: Differentiated Teachers Guided Self-Supervised Video Action Recognition0
DWnet: Deep-Wide Network for 3D Action Recognition0
Dynamic Action Recognition: A convolutional neural network model for temporally organized joint location data0
Dynamically Encoded Actions Based on Spacetime Saliency0
Dynamic Appearance: A Video Representation for Action Recognition with Joint Training0
Dynamic Graph Modules for Modeling Object-Object Interactions in Activity Recognition0
Dynamic Hypergraph Convolutional Networks for Skeleton-Based Action Recognition0
Dynamic Inference: A New Approach Toward Efficient Video Action Recognition0
Dynamic Matrix Decomposition for Action Recognition0
Dynamic Probabilistic Network Based Human Action Recognition0
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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