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 18011825 of 2759 papers

TitleStatusHype
Sparse Dictionary-based Attributes for Action Recognition and Summarization0
Sparse Models for Machine Learning0
Sparse Semi-Supervised Action Recognition with Active Learning0
Spatial Residual Layer and Dense Connection Block Enhanced Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition0
Spatial-Temporal Alignment Network for Action Recognition and Detection0
Spatial-Temporal Alignment Network for Action Recognition0
Spatial-Temporal Pyramid Graph Reasoning for Action Recognition0
Spatial-Temporal Transformer for 3D Point Cloud Sequences0
Spatial-temporal Transformer-guided Diffusion based Data Augmentation for Efficient Skeleton-based Action Recognition0
Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition0
Spatio-temporal Action Recognition: A Survey0
Spatiotemporal Attention-based Semantic Compression for Real-time Video Recognition0
Frequency Selective Augmentation for Video Representation Learning0
Spatio-temporal Aware Non-negative Component Representation for Action Recognition0
Spatio-temporal Contrastive Domain Adaptation for Action Recognition0
Spatiotemporal Decouple-and-Squeeze Contrastive Learning for Semi-Supervised Skeleton-based Action Recognition0
Spatio-Temporal Dual Affine Differential Invariant for Skeleton-based Action Recognition0
Spatio-Temporal FAST 3D Convolutions for Human Action Recognition0
Spatiotemporal Filtering for Event-Based Action Recognition0
SpatioTemporal Focus for Skeleton-based Action Recognition0
Spatiotemporal Fusion in 3D CNNs: A Probabilistic View0
Spatio-Temporal Fusion Networks for Action Recognition0
Spatio-Temporal Graph Complementary Scattering Networks0
Spatio-Temporal Graph Convolution for Skeleton Based Action Recognition0
Spatiotemporal graph routing for skeleton-based action recognition0
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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