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

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Showing 1601–1650 of 2759 papers

TitleStatusHype
Online Recognition of Actions Involving ObjectsCode0
Event-based Timestamp Image Encoding Network for Human Action Recognition and Anticipation—0
Learning Chebyshev Basis in Graph Convolutional Networks for Skeleton-based Action Recognition—0
Few-Shot Action Recognition with Compromised Metric via Optimal Transport—0
Self-supervised Video Representation Learning by Context and Motion DecouplingCode0
Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories—0
Self-supervised Motion Learning from Static Images—0
Selective Feature Compression for Efficient Activity Recognition Inference—0
Composable Augmentation Encoding for Video Representation Learning—0
Motion Guided Attention Fusion to Recognize Interactions from Videos—0
Weakly Supervised Temporal Action Localization Through Learning Explicit Subspaces for Action and Context—0
Recognizing Actions in Videos from Unseen Viewpoints—0
Robust Audio-Visual Instance Discrimination—0
GPRAR: Graph Convolutional Network based Pose Reconstruction and Action Recognition for Human Trajectory PredictionCode0
Learning Comprehensive Motion Representation for Action Recognition—0
AdaSGN: Adapting Joint Number and Model Size for Efficient Skeleton-Based Action Recognition—0
Efficient Spatialtemporal Context Modeling for Action Recognition—0
Deep Learning for Vision-Based Fall Detection System: Enhanced Optical Dynamic Flow—0
CLTA: Contents and Length-based Temporal Attention for Few-shot Action Recognition—0
NAS-TC: Neural Architecture Search on Temporal Convolutions for Complex Action Recognition—0
Unsupervised Motion Representation Enhanced Network for Action Recognition—0
Domain Generalization: A Survey—0
DeepFN: Towards Generalizable Facial Action Unit Recognition with Deep Face Normalization—0
Domain and View-point Agnostic Hand Action RecognitionCode0
Phase Space Reconstruction Network for Lane Intrusion Action Recognition—0
Self-Supervised Learning via multi-Transformation Classification for Action Recognition—0
A Temporal Fusion Approach for Video Classification with Convolutional and LSTM Neural Networks Applied to Violence Detection—0
Learning to Recognize Actions on Objects in Egocentric Video with Attention Dictionaries—0
Win-Fail Action RecognitionCode0
AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition—0
Video Action Recognition Using spatio-temporal optical flow video frames—0
GCF-Net: Gated Clip Fusion Network for Video Action Recognition—0
Video Transformer NetworkCode0
Optical flow and scene flow estimation: A survey—0
Embedding Symbolic Temporal Knowledge into Deep Sequential Models—0
SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models—0
A Two-stream Neural Network for Pose-based Hand Gesture Recognition—0
Bridging the gap between Human Action Recognition and Online Action Detection—0
Human Action Recognition Based on Multi-scale Feature Maps from Depth Video Sequences—0
CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition—0
Video action recognition for lane-change classification and prediction of surrounding vehicles—0
Learning from Weakly-labeled Web Videos via Exploring Sub-Concepts—0
Trear: Transformer-based RGB-D Egocentric Action Recognition—0
Temporal Contrastive Graph Learning for Video Action Recognition and Retrieval—0
Transformers in Vision: A Survey—0
Uncertainty-sensitive Activity Recognition: a Reliability Benchmark and the CARING Models—0
Contrast and Order Representations for Video Self-Supervised Learning—0
Exploring Sub-Pseudo Labels for Learning from Weakly-Labeled Web Videos—0
Beyond the Pixels: Exploring the Effects of Bit-Level Network and File Corruptions on Video Model Robustness—0
Else-Net: Elastic Semantic Network for Continual Action Recognition From Skeleton Data—0
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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