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 14511475 of 2759 papers

TitleStatusHype
Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action RecognitionCode1
NTU-X: An Enhanced Large-scale Dataset for Improving Pose-based Recognition of Subtle Human ActionsCode1
SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models0
A Two-stream Neural Network for Pose-based Hand Gesture Recognition0
Bridging the gap between Human Action Recognition and Online Action Detection0
TCLR: Temporal Contrastive Learning for Video RepresentationCode1
Few-shot Action Recognition with Prototype-centered Attentive LearningCode1
ArtEmis: Affective Language for Visual ArtCode1
Human Action Recognition Based on Multi-scale Feature Maps from Depth Video Sequences0
CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition0
Temporal-Relational CrossTransformers for Few-Shot Action RecognitionCode1
Video action recognition for lane-change classification and prediction of surrounding vehicles0
Temporally Guided Articulated Hand Pose Tracking in Surgical VideosCode1
Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts0
Trear: Transformer-based RGB-D Egocentric Action Recognition0
Temporal Contrastive Graph Learning for Video Action Recognition and Retrieval0
Transformers in Vision: A Survey0
Uncertainty-sensitive Activity Recognition: a Reliability Benchmark and the CARING Models0
Refining activation downsampling with SoftPoolCode1
Vi2CLR: Video and Image for Visual Contrastive Learning of Representation0
Else-Net: Elastic Semantic Network for Continual Action Recognition From Skeleton Data0
Efficient Action Recognition via Dynamic Knowledge Propagation0
Interactive Prototype Learning for Egocentric Action Recognition0
Self-Supervised 3D Skeleton Action Representation Learning With Motion Consistency and Continuity0
Contrast and Order Representations for Video Self-Supervised Learning0
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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