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 201225 of 2759 papers

TitleStatusHype
Grad-CAM++: Improved Visual Explanations for Deep Convolutional NetworksCode1
Graph Contrastive Learning for Skeleton-based Action RecognitionCode1
EAN: Event Adaptive Network for Enhanced Action RecognitionCode1
Complex Sequential Understanding through the Awareness of Spatial and Temporal ConceptsCode1
EgoAdapt: A multi-stream evaluation study of adaptation to real-world egocentric user videoCode1
Compressing Recurrent Neural Networks with Tensor Ring for Action RecognitionCode1
Conquering the cnn over-parameterization dilemma: A volterra filtering approach for action recognitionCode1
Volterra Neural Networks (VNNs)Code1
Constructing Stronger and Faster Baselines for Skeleton-based Action RecognitionCode1
A Large-scale Study of Spatiotemporal Representation Learning with a New Benchmark on Action RecognitionCode1
A Large-Scale Study on Video Action Dataset CondensationCode1
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action RecognitionCode1
Hear Me Out: Fusional Approaches for Audio Augmented Temporal Action LocalizationCode1
Hidden Two-Stream Convolutional Networks for Action RecognitionCode1
ArtEmis: Affective Language for Visual ArtCode1
A Unified Multimodal De- and Re-coupling Framework for RGB-D Motion RecognitionCode1
ConvNet Architecture Search for Spatiotemporal Feature LearningCode1
Hierarchical Temporal Transformer for 3D Hand Pose Estimation and Action Recognition from Egocentric RGB VideosCode1
A Closer Look at Spatiotemporal Convolutions for Action RecognitionCode1
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical AggregationCode1
Counterfactual Debiasing Inference for Compositional Action RecognitionCode1
A Local-to-Global Approach to Multi-modal Movie Scene SegmentationCode1
ViViT: A Video Vision TransformerCode1
D^2ST-Adapter: Disentangled-and-Deformable Spatio-Temporal Adapter for Few-shot Action RecognitionCode1
Action Transformer: A Self-Attention Model for Short-Time Pose-Based Human Action RecognitionCode1
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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