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 301325 of 2759 papers

TitleStatusHype
Spatio-temporal Relation Modeling for Few-shot Action RecognitionCode1
Prompting Visual-Language Models for Efficient Video UnderstandingCode1
Topology-aware Convolutional Neural Network for Efficient Skeleton-based Action RecognitionCode1
Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action RecognitionCode1
TCGL: Temporal Contrastive Graph for Self-supervised Video Representation LearningCode1
E^2(GO)MOTION: Motion Augmented Event Stream for Egocentric Action RecognitionCode1
Self-supervised Video TransformerCode1
BEVT: BERT Pretraining of Video TransformersCode1
MViTv2: Improved Multiscale Vision Transformers for Classification and DetectionCode1
MAU: A Motion-Aware Unit for Video Prediction and BeyondCode1
Anonymization for Skeleton Action RecognitionCode1
Learning from Temporal Gradient for Semi-supervised Action RecognitionCode1
Florence: A New Foundation Model for Computer VisionCode1
M2A: Motion Aware Attention for Accurate Video Action RecognitionCode1
Real-time 3D human action recognition based on Hyperpoint sequenceCode1
UBnormal: New Benchmark for Supervised Open-Set Video Anomaly DetectionCode1
Relational Self-Attention: What's Missing in Attention for Video UnderstandingCode1
Revisiting spatio-temporal layouts for compositional action recognitionCode1
With a Little Help from my Temporal Context: Multimodal Egocentric Action RecognitionCode1
Logsig-RNN: a novel network for robust and efficient skeleton-based action recognitionCode1
LSTC: Boosting Atomic Action Detection with Long-Short-Term ContextCode1
Counterfactual Debiasing Inference for Compositional Action RecognitionCode1
Object-Region Video TransformersCode1
Sign Language Recognition via Skeleton-Aware Multi-Model EnsembleCode1
Motion-aware Contrastive Video Representation Learning via Foreground-background MergingCode1
Show:102550
← PrevPage 13 of 111Next →

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