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 926950 of 2759 papers

TitleStatusHype
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
I3D-LSTM: A New Model for Human Action RecognitionCode0
Idempotent Unsupervised Representation Learning for Skeleton-Based Action RecognitionCode0
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
Cross-modal Learning by Hallucinating Missing Modalities in RGB-D VisionCode0
Cross-modal Knowledge Distillation for Vision-to-Sensor Action RecognitionCode0
Analysis of Hand Segmentation in the WildCode0
Cross-Modal and Hierarchical Modeling of Video and TextCode0
Human activity recognition from skeleton posesCode0
HomE: Homography-Equivariant Video Representation LearningCode0
H-MoRe: Learning Human-centric Motion Representation for Action AnalysisCode0
Actions ~ TransformationsCode0
HopaDIFF: Holistic-Partial Aware Fourier Conditioned Diffusion for Referring Human Action Segmentation in Multi-Person ScenariosCode0
A Recurrent Transformer Network for Novel View Action SynthesisCode0
Cross and Learn: Cross-Modal Self-SupervisionCode0
Are current long-term video understanding datasets long-term?Code0
High-Performance Inference Graph Convolutional Networks for Skeleton-Based Action RecognitionCode0
HPERL: 3D Human Pose Estimation from RGB and LiDARCode0
Counterfactual Gradients-based Quantification of Prediction Trust in Neural NetworksCode0
Temporal Unet: Sample Level Human Action Recognition using WiFiCode0
Fine-grained Affordance Annotation for Egocentric Hand-Object Interaction VideosCode0
Action Selection Learning for Multi-label Multi-view Action RecognitionCode0
CoTeRe-Net: Discovering Collaborative Ternary Relations in VideosCode0
Temporal-Channel Topology Enhanced Network for Skeleton-Based Action RecognitionCode0
Hierarchical Explanations for Video Action RecognitionCode0
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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