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 10261050 of 2759 papers

TitleStatusHype
Action Recognition for American Sign Language0
PSO-Convolutional Neural Networks with Heterogeneous Learning RateCode0
PYSKL: Towards Good Practices for Skeleton Action Recognition0
Noise-Tolerant Learning for Audio-Visual Action Recognition0
Video-ReTime: Learning Temporally Varying Speediness for Time Remapping0
Representation Learning for Compressed Video Action Recognition via Attentive Cross-modal Interaction with Motion Enhancement0
Handcrafted localized phase features for human action recognition0
TransRank: Self-supervised Video Representation Learning via Ranking-based Transformation RecognitionCode1
ANUBIS: Skeleton Action Recognition Dataset, Review, and Benchmark0
Cross-modal Representation Learning for Zero-shot Action Recognition0
Preserve Pre-trained Knowledge: Transfer Learning With Self-Distillation For Action Recognition0
On Negative Sampling for Audio-Visual Contrastive Learning from Movies0
Hybrid Relation Guided Set Matching for Few-shot Action RecognitionCode1
Self-supervised Contrastive Learning for Audio-Visual Action Recognition0
HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling0
Human-Centered Prior-Guided and Task-Dependent Multi-Task Representation Learning for Action Recognition Pre-Training0
MILES: Visual BERT Pre-training with Injected Language Semantics for Video-text RetrievalCode1
Temporal Relevance Analysis for Video Action Models0
iCAR: Bridging Image Classification and Image-text Alignment for Visual RecognitionCode0
Unsupervised Human Action Recognition with Skeletal Graph Laplacian and Self-Supervised Viewpoints InvarianceCode0
STAU: A SpatioTemporal-Aware Unit for Video Prediction and Beyond0
FenceNet: Fine-grained Footwork Recognition in Fencing0
THORN: Temporal Human-Object Relation Network for Action Recognition0
A Survey of Video-based Action Quality Assessment0
Performance Evaluation of Action Recognition Models on Low Quality Videos0
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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