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 1901–1950 of 2759 papers

TitleStatusHype
A Real-time Action Representation with Temporal Encoding and Deep Compression—0
A real-time algorithm for human action recognition in RGB and thermal video—0
A Real-Time System for Egocentric Hand-Object Interaction Detection in Industrial Domains—0
A Review on Coarse to Fine-Grained Animal Action Recognition—0
Are Visual-Language Models Effective in Action Recognition? A Comparative Study—0
Are you SURE? Enhancing Multimodal Pretraining with Missing Modalities through Uncertainty Estimation—0
ARN-LSTM: A Multi-Stream Fusion Model for Skeleton-based Action Recognition—0
A robust and efficient video representation for action recognition—0
ARTiS: Appearance-based Action Recognition in Task Space for Real-Time Human-Robot Collaboration—0
ASCNet: Self-supervised Video Representation Learning with Appearance-Speed Consistency—0
A Semantics-Guided Graph Convolutional Network for Skeleton-Based Action Recognition—0
A Short Overview of Multi-Modal Wi-Fi Sensing—0
A Simple and Efficient Baseline for Video Action Recognition—0
ASL Recognition with Metric-Learning based Lightweight Network—0
A Spectral Nonlocal Block for Neural Networks—0
A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2023—0
A Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP—0
A Survey of IMU Based Cross-Modal Transfer Learning in Human Activity Recognition—0
A Survey of Video-based Action Quality Assessment—0
A Survey of Visual Analysis of Human Motion and Its Applications—0
A Survey on 3D Skeleton-Based Action Recognition Using Learning Method—0
A Survey on Backbones for Deep Video Action Recognition—0
A Survey on Contrastive Self-supervised Learning—0
A Survey on Human Action Recognition—0
A Survey on Multimodal Wearable Sensor-based Human Action Recognition—0
A Survey on Wi-Fi Sensing Generalizability: Taxonomy, Techniques, Datasets, and Future Research Prospects—0
A Temporal Fusion Approach for Video Classification with Convolutional and LSTM Neural Networks Applied to Violence Detection—0
A Temporal Sequence Learning for Action Recognition and Prediction—0
AtGCN: A Graph Convolutional Network For Ataxic Gait Detection—0
A Training Method For VideoPose3D With Ideology of Action Recognition—0
ATTACH Dataset: Annotated Two-Handed Assembly Actions for Human Action Understanding—0
Attend and Interact: Higher-Order Object Interactions for Video Understanding—0
Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition—0
Attention-Oriented Action Recognition for Real-Time Human-Robot Interaction—0
Attention Spiking Neural Networks—0
Attention Transfer from Web Images for Video Recognition—0
Attentive Action and Context Factorization—0
Attributes' Importance for Zero-Shot Pose-Classification Based on Wearable Sensors—0
A Tube-and-Droplet-based Approach for Representing and Analyzing Motion Trajectories—0
A Two-stream Neural Network for Pose-based Hand Gesture Recognition—0
Self-supervised Contrastive Learning for Audio-Visual Action Recognition—0
Audio-Visual Contrastive Learning with Temporal Self-Supervision—0
Augmenting and Aligning Snippets for Few-Shot Video Domain Adaptation—0
A Unified Deep Framework for Joint 3D Pose Estimation and Action Recognition from a Single RGB Camera—0
A Unified Framework for Human-centric Point Cloud Video Understanding—0
A Unified Framework to Analyze and Design the Nonlocal Blocks for Neural Networks—0
A Unified Method for First and Third Person Action Recognition—0
A Unified Model Selection Technique for Spectral Clustering Based Motion Segmentation—0
Automatic Curation of Golf Highlights using Multimodal Excitement Features—0
Automatic evaluation of herding behavior in towed fishing gear using end-to-end training of CNN and attention-based networks—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