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 14261450 of 2759 papers

TitleStatusHype
Representing Videos as Discriminative Sub-graphs for Action Recognition0
Boosting Video Representation Learning with Multi-Faceted Integration0
Interact Before Align: Leveraging Cross-Modal Knowledge for Domain Adaptive Action Recognition0
Multi-Grained Spatio-Temporal Features Perceived Network for Event-Based Lip-Reading0
Learning Video Representations of Human Motion From Synthetic Data0
Recurring the Transformer for Video Action Recognition0
Object-Relation Reasoning Graph for Action Recognition0
Complex Video Action Reasoning via Learnable Markov Logic Network0
Uncertainty-Guided Probabilistic Transformer for Complex Action Recognition0
Motion-Modulated Temporal Fragment Alignment Network for Few-Shot Action Recognition0
3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve0
Recur, Attend or Convolve? On Whether Temporal Modeling Matters for Cross-Domain Robustness in Action RecognitionCode0
Fine-grained Multi-Modal Self-Supervised Learning0
Expansion-Squeeze-Excitation Fusion Network for Elderly Activity Recognition0
Dynamic Hypergraph Convolutional Networks for Skeleton-Based Action Recognition0
Precondition and Effect Reasoning for Action RecognitionCode0
Cross-Model Pseudo-Labeling for Semi-Supervised Action Recognition0
Self-attention based anchor proposal for skeleton-based action recognition0
Distillation of Human-Object Interaction Contexts for Action Recognition0
Analysis and Evaluation of Kinect-based Action Recognition AlgorithmsCode0
Temporal Shuffling for Defending Deep Action Recognition Models against Adversarial AttacksCode0
Detecting Object States vs Detecting Objects: A New Dataset and a Quantitative Experimental StudyCode0
Temporal Transformer Networks with Self-Supervision for Action Recognition0
Co-training Transformer with Videos and Images Improves Action Recognition0
Real Time Action Recognition from Video Footage0
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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