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 751775 of 2759 papers

TitleStatusHype
Local Spherical Harmonics Improve Skeleton-Based Hand Action RecognitionCode0
Lightweight Recurrent Cross-modal Encoder for Video Question AnsweringCode0
LoCATe-GAT: Modeling Multi-Scale Local Context and Action Relationships for Zero-Shot Action RecognitionCode0
Let's Dance: Learning From Online Dance VideosCode0
Discriminating Spatial and Temporal Relevance in Deep Taylor Decompositions for Explainable Activity RecognitionCode0
Learning Visual Actions Using Multiple Verb-Only LabelsCode0
Learning with privileged information via adversarial discriminative modality distillationCode0
Learn to cycle: Time-consistent feature discovery for action recognitionCode0
Skeleton-OOD: An End-to-End Skeleton-Based Model for Robust Out-of-Distribution Human Action DetectionCode0
Learning To Score Olympic EventsCode0
Learning to Estimate Pose by Watching VideosCode0
Bayesian Hierarchical Dynamic Model for Human Action RecognitionCode0
Learning Video Representations from Correspondence ProposalsCode0
Audio-Visual Scene Analysis with Self-Supervised Multisensory FeaturesCode0
DG-STGCN: Dynamic Spatial-Temporal Modeling for Skeleton-based Action RecognitionCode0
Learning Spatio-Temporal Features with 3D Residual Networks for Action RecognitionCode0
Learning Spatio-Temporal Representation with Local and Global DiffusionCode0
Audio-Visual Model Distillation Using Acoustic ImagesCode0
Learning Skeletal Graph Neural Networks for Hard 3D Pose EstimationCode0
DetReIDX: A Stress-Test Dataset for Real-World UAV-Based Person RecognitionCode0
Learning long-term dependencies for action recognition with a biologically-inspired deep networkCode0
Learning Mutual Excitation for Hand-to-Hand and Human-to-Human Interaction RecognitionCode0
Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural SearchingCode0
Detecting the Starting Frame of Actions in VideoCode0
Learning Human Action Recognition Representations Without Real HumansCode0
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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