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 15511575 of 2759 papers

TitleStatusHype
On the spatial attention in Spatio-Temporal Graph Convolutional Networks for skeleton-based human action recognitionCode1
Mutual Modality Learning for Video Action ClassificationCode1
Learning Representations from Audio-Visual Spatial Alignment0
Memory Group Sampling Based Online Action Recognition Using Kinetic Skeleton Features0
A Survey on Contrastive Self-supervised Learning0
Bubblenet: A Disperse Recurrent Structure To Recognize Activities0
Pose-based Body Language Recognition for Emotion and Psychiatric Symptom Interpretation0
CNN based Multistage Gated Average Fusion (MGAF) for Human Action Recognition Using Depth and Inertial SensorsCode0
SAR-NAS: Skeleton-based Action Recognition via Neural Architecture Searching0
ElderSim: A Synthetic Data Generation Platform for Human Action Recognition in Eldercare Applications0
Cycle-Contrast for Self-Supervised Video Representation Learning0
RSPNet: Relative Speed Perception for Unsupervised Video Representation LearningCode1
Nested Grassmannians for Dimensionality Reduction with ApplicationsCode0
View-Invariant, Occlusion-Robust Probabilistic Embedding for Human PoseCode0
Temporal Attention-Augmented Graph Convolutional Network for Efficient Skeleton-Based Human Action Recognition0
Deep Analysis of CNN-based Spatio-temporal Representations for Action RecognitionCode1
Learning to Sort Image Sequences via Accumulated Temporal Differences0
Stronger, Faster and More Explainable: A Graph Convolutional Baseline for Skeleton-based Action RecognitionCode1
Depth Guided Adaptive Meta-Fusion Network for Few-shot Video RecognitionCode1
Self-supervised Co-training for Video Representation LearningCode1
Temporal Binary Representation for Event-Based Action RecognitionCode0
A Grid-based Representation for Human Action Recognition0
Toward Accurate Person-level Action Recognition in Videos of Crowded Scenes0
What Can You Learn from Your Muscles? Learning Visual Representation from Human InteractionsCode1
HPERL: 3D Human Pose Estimation from RGB and LiDARCode0
Show:102550
← PrevPage 63 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