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 20762100 of 2759 papers

TitleStatusHype
Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition0
Weakly-Supervised Multi-Person Action Recognition in 360^ Videos0
Weakly Supervised Recognition of Surgical Gestures0
Weakly Supervised Temporal Action Localization Through Learning Explicit Subspaces for Action and Context0
We Can "See" You via Wi-Fi - WiFi Action Recognition via Vision-based Methods0
What can a cook in Italy teach a mechanic in India? Action Recognition Generalisation Over Scenarios and Locations0
What do 15,000 Object Categories Tell Us About Classifying and Localizing Actions?0
What have we learned from deep representations for action recognition?0
When Kernel Methods meet Feature Learning: Log-Covariance Network for Action Recognition from Skeletal Data0
When Spatial meets Temporal in Action Recognition0
Where and when to look? Spatial-temporal attention for action recognition in videos0
WOAD: Weakly Supervised Online Action Detection in Untrimmed Videos0
Word-level Sign Language Recognition with Multi-stream Neural Networks Focusing on Local Regions and Skeletal Information0
X-ToM: Explaining with Theory-of-Mind for Gaining Justified Human Trust0
X-VARS: Introducing Explainability in Football Refereeing with Multi-Modal Large Language Model0
YH Technologies at ActivityNet Challenge 20180
You Lead, We Exceed: Labor-Free Video Concept Learning by Jointly Exploiting Web Videos and Images0
Your head is there to move you around: Goal-driven models of the primate dorsal pathway0
Zero-Shot Action Recognition in Surveillance Videos0
Zero-Shot Action Recognition in Videos: A Survey0
Zero-Shot Action Recognition With Error-Correcting Output Codes0
Zero-Shot Activity Recognition with Videos0
Training-Free Action Recognition and Goal Inference with Dynamic Frame Selection0
Zero-Shot Skeleton-based Action Recognition with Dual Visual-Text Alignment0
Zero-Shot Visual Recognition via Bidirectional Latent Embedding0
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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