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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1501–1550 of 2759 papers

TitleStatusHype
Cross-modal Knowledge Distillation for Vision-to-Sensor Action RecognitionCode0
A Baseline Framework for Part-level Action Parsing and Action Recognition—0
A Multi-viewpoint Outdoor Dataset for Human Action RecognitionCode0
SAIC_Cambridge-HuPBA-FBK Submission to the EPIC-Kitchens-100 Action Recognition Challenge 2021—0
Construction Site Safety Monitoring and Excavator Activity Analysis System—0
Efficient Modelling Across Time of Human Actions and Interactions—0
Procedure Planning in Instructional Videos via Contextual Modeling and Model-based Policy Learning—0
Spatio-Temporal Video Representation Learning for AI Based Video Playback Style Prediction—0
Unsupervised Motion Representation Learning with Capsule AutoencodersCode0
Deep Learning-based Action Detection in Untrimmed Videos: A Survey—0
Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark—0
Unsupervised Few-Shot Action Recognition via Action-Appearance Aligned Meta-Adaptation—0
Transductive Universal Transport for Zero-Shot Action Recognition—0
Vi-MIX FOR SELF-SUPERVISED VIDEO REPRESENTATION—0
Fundamental Limits of Transfer Learning in Binary Classifications—0
Cross-Stage Transformer for Video Learning—0
Self-Supervised Learning of Motion-Informed Latents—0
Information Elevation Network for Fast Online Action Detection—0
Self-Supervised Video Representation Learning by Video Incoherence Detection—0
Long Short View Feature Decomposition via Contrastive Video Representation Learning—0
Unsupervised View-Invariant Human Posture Representation—0
Adversarial Bone Length Attack on Action Recognition—0
Egocentric View Hand Action Recognition by Leveraging Hand Surface and Hand Grasp Type—0
Hierarchical Graph Convolutional Skeleton Transformer for Action Recognition—0
Efficient Action Recognition Using Confidence Distillation—0
Conditional Extreme Value Theory for Open Set Video Domain AdaptationCode0
LIGAR: Lightweight General-purpose Action Recognition—0
Shifted Chunk Transformer for Spatio-Temporal Representational Learning—0
Learning Cross-modal Contrastive Features for Video Domain Adaptation—0
BiaSwap: Removing dataset bias with bias-tailored swapping augmentation—0
MM-ViT: Multi-Modal Video Transformer for Compressed Video Action Recognition—0
Few Shot Activity Recognition Using Variational Inference—0
Self-Supervised Video Representation Learning with Meta-Contrastive Network—0
The Multi-Modal Video Reasoning and Analyzing Competition—0
Channel-Temporal Attention for First-Person Video Domain Adaptation—0
Learning Skeletal Graph Neural Networks for Hard 3D Pose EstimationCode0
Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-LearningCode0
Temporal Action Segmentation with High-level Complex Activity Labels—0
Learning Visual Affordance Grounding from Demonstration Videos—0
Spatio-Temporal Human Action Recognition Modelwith Flexible-interval Sampling and Normalization—0
Temporal Action Localization Using Gated Recurrent UnitsCode0
Feature-Supervised Action Modality Transfer—0
Skeleton Cloud Colorization for Unsupervised 3D Action Representation Learning—0
Classifying action correctness in physical rehabilitation exercises—0
Lighter Stacked Hourglass Human Pose Estimation—0
A New Split for Evaluating True Zero-Shot Action RecognitionCode0
Adaptive Recursive Circle Framework for Fine-grained Action Recognition—0
Federated Action Recognition on Heterogeneous Embedded Devices—0
LSFB-CONT and LSFB-ISOL: Two New Datasets for Vision-Based Sign Language RecognitionCode0
Group Activity Recognition Using Joint Learning of Individual Action Recognition and People GroupingCode0
Show:102550
← PrevPage 31 of 56Next →
All datasetsSomething-Something V2UCF101HMDB-51Something-Something V1AVA v2.2EPIC-KITCHENS-100NTU RGB+DNTU RGB+D 120Diving-48ActivityNetAVA v2.1H2O (2 Hands and Objects)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MViTv2-B (IN-21K + Kinetics400 pretrain)Top-5 Accuracy93.4—Unverified
2RSANet-R50 (8+16 frames, ImageNet pretrained, 2 clips)Top-5 Accuracy91.1—Unverified
3MVD (Kinetics400 pretrain, ViT-H, 16 frame)Top-1 Accuracy77.3—Unverified
4DejaVidTop-1 Accuracy77.2—Unverified
5InternVideoTop-1 Accuracy77.2—Unverified
6InternVideo2-1BTop-1 Accuracy77.1—Unverified
7VideoMAE V2-gTop-1 Accuracy77—Unverified
8MVD (Kinetics400 pretrain, ViT-L, 16 frame)Top-1 Accuracy76.7—Unverified
9Hiera-L (no extra data)Top-1 Accuracy76.5—Unverified
10TubeViT-LTop-1 Accuracy76.1—Unverified
#ModelMetricClaimedVerifiedStatus
1FTP-UniFormerV2-L/143-fold Accuracy99.7—Unverified
2OmniVec23-fold Accuracy99.6—Unverified
3VideoMAE V2-g3-fold Accuracy99.6—Unverified
4OmniVec3-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
8PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
9ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
10LGD-3D Two-stream3-fold Accuracy98.2—Unverified