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
Just One Moment: Structural Vulnerability of Deep Action Recognition against One Frame Attack0
Annotation-Efficient Untrimmed Video Action Recognition0
Depth-Aware Action Recognition: Pose-Motion Encoding through Temporal Heatmaps0
Group-Skeleton-Based Human Action Recognition in Complex Events0
Spatio-Temporal Inception Graph Convolutional Networks for Skeleton-Based Action RecognitionCode1
Recent Progress in Appearance-based Action Recognition0
Independent Sign Language Recognition with 3D Body, Hands, and Face Reconstruction0
A3D: Adaptive 3D Networks for Video Action Recognition0
Play Fair: Frame Attributions in Video ModelsCode1
KShapeNet: Riemannian network on Kendall shape space for Skeleton based Action Recognition0
Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning0
Modular Action Concept Grounding in Semantic Video Prediction0
Learnable Sampling 3D Convolution for Video Enhancement and Action Recognition0
Semi-Supervised Few-Shot Atomic Action RecognitionCode1
3D CNNs with Adaptive Temporal Feature ResolutionsCode1
DARE: AI-based Diver Action Recognition System using Multi-Channel CNNs for AUV Supervision0
JOLO-GCN: Mining Joint-Centered Light-Weight Information for Skeleton-Based Action Recognition0
Human activity recognition using improved dynamic image0
Prototypical Contrast and Reverse Prediction: Unsupervised Skeleton Based Action RecognitionCode0
Unsupervised Video Representation Learning by Bidirectional Feature Prediction0
Progressive Spatio-Temporal Graph Convolutional Network for Skeleton-Based Human Action Recognition0
Selective Spatio-Temporal Aggregation Based Pose Refinement System: Towards Understanding Human Activities in Real-World VideosCode1
Integrating Human Gaze into Attention for Egocentric Activity RecognitionCode1
Multi-Temporal Convolutions for Human Action Recognition in VideosCode1
FlowCaps: Optical Flow Estimation with Capsule Networks For 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
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