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 501550 of 2759 papers

TitleStatusHype
Concatenated Masked Autoencoders as Spatial-Temporal LearnerCode1
ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab0
Distribution of Action Movements (DAM): A Descriptor for Human Action Recognition0
IndustReal: A Dataset for Procedure Step Recognition Handling Execution Errors in Egocentric Videos in an Industrial-Like SettingCode1
Videoprompter: an ensemble of foundational models for zero-shot video understanding0
S3Aug: Segmentation, Sampling, and Shift for Action Recognition0
Is Weakly-supervised Action Segmentation Ready For Human-Robot Interaction? No, Let's Improve It With Action-union LearningCode2
Human Pose-based Estimation, Tracking and Action Recognition with Deep Learning: A Survey0
Frozen Transformers in Language Models Are Effective Visual Encoder LayersCode2
Deep Learning Techniques for Video Instance Segmentation: A Survey0
InfoGCN++: Learning Representation by Predicting the Future for Online Human Skeleton-based Action RecognitionCode1
Flow Dynamics Correction for Action Recognition0
3DYoga90: A Hierarchical Video Dataset for Yoga Pose UnderstandingCode1
Few-shot Action Recognition with Captioning Foundation Models0
Proving the Potential of Skeleton Based Action Recognition to Automate the Analysis of Manual Processes0
SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition0
Language Model Beats Diffusion -- Tokenizer is Key to Visual GenerationCode4
Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and DataCode1
Analyzing Zero-Shot Abilities of Vision-Language Models on Video Understanding Tasks0
Graph learning in robotics: a survey0
PoseAction: Action Recognition for Patients in the Ward using Deep Learning Approaches0
Beyond the Benchmark: Detecting Diverse Anomalies in VideosCode0
ZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to VideoCode1
Action Recognition Utilizing YGAR Dataset0
A Hierarchical Graph-based Approach for Recognition and Description Generation of Bimanual Actions in Videos0
Telling Stories for Common Sense Zero-Shot Action RecognitionCode0
Training a Large Video Model on a Single Machine in a DayCode1
Position and Orientation-Aware One-Shot Learning for Medical Action Recognition from Signal Data0
End-to-End Streaming Video Temporal Action Segmentation with Reinforce LearningCode1
M^33D: Learning 3D priors using Multi-Modal Masked Autoencoders for 2D image and video understanding0
Chop & Learn: Recognizing and Generating Object-State Compositions0
Boundary-Aware Proposal Generation Method for Temporal Action Localization0
Egocentric RGB+Depth Action Recognition in Industry-Like SettingsCode0
S3TC: Spiking Separated Spatial and Temporal Convolutions with Unsupervised STDP-based Learning for Action Recognition0
Survey of Action Recognition, Spotting and Spatio-Temporal Localization in Soccer -- Current Trends and Research Perspectives0
Exploring Self-supervised Skeleton-based Action Recognition in Occluded EnvironmentsCode1
CPR-Coach: Recognizing Composite Error Actions based on Single-class Training0
Elevating Skeleton-Based Action Recognition with Efficient Multi-Modality Self-SupervisionCode0
SkeleTR: Towrads Skeleton-based Action Recognition in the Wild0
Language as the Medium: Multimodal Video Classification through text only0
Selective Volume Mixup for Video Action RecognitionCode0
Multi-Semantic Fusion Model for Generalized Zero-Shot Skeleton-Based Action RecognitionCode1
CaSAR: Contact-aware Skeletal Action Recognition0
Towards Debiasing Frame Length Bias in Text-Video Retrieval via Causal Intervention0
hear-your-action: human action recognition by ultrasound active sensing0
TransNet: A Transfer Learning-Based Network for Human Action Recognition0
Grounded Language Acquisition From Object and Action Imagery0
SCD-Net: Spatiotemporal Clues Disentanglement Network for Self-supervised Skeleton-based Action Recognition0
Unified Contrastive Fusion Transformer for Multimodal Human Action Recognition0
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
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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