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 24262450 of 2759 papers

TitleStatusHype
hear-your-action: human action recognition by ultrasound active sensing0
HENASY: Learning to Assemble Scene-Entities for Egocentric Video-Language Model0
Heterogeneous Skeleton-Based Action Representation Learning0
HFGCN:Hypergraph Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition0
Hidden Markov Model: Tutorial0
Hierarchical Action Classification with Network Pruning0
Hierarchical Action Recognition: A Contrastive Video-Language Approach with Hierarchical Interactions0
CoSimGNN: Towards Large-scale Graph Similarity Computation0
Hierarchical Attention Network for Action Recognition in Videos0
Hierarchical Compositional Representations for Few-shot Action Recognition0
Hierarchical Contrastive Motion Learning for Video Action Recognition0
Hierarchical Feature Aggregation Networks for Video Action Recognition0
Hierarchical Long Short-Term Concurrent Memory for Human Interaction Recognition0
Hierarchically Decoupled Spatial-Temporal Contrast for Self-supervised Video Representation Learning0
Hierarchically Learned View-Invariant Representations for Cross-View Action Recognition0
Hierarchical Multi-scale Attention Networks for Action Recognition0
Hierarchical recurrent neural network for skeleton based action recognition0
Hierarchical Self-supervised Representation Learning for Movie Understanding0
Hierarchical Spatial Sum-Product Networks for Action Recognition in Still Images0
Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition0
Highly Efficient Human Action Recognition with Quantum Genetic Algorithm Optimized Support Vector Machine0
Higher-order Network for Action Recognition0
High-order Tensor Pooling with Attention for Action Recognition0
High Speed Human Action Recognition using a Photonic Reservoir Computer0
Histogram of Oriented Depth Gradients for 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