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 1201–1250 of 2759 papers

TitleStatusHype
Deep Discriminative Model for Video Classification—0
Deep Convolutional Neural Networks for Action Recognition Using Depth Map Sequences—0
Integrating Audio Narrations to Strengthen Domain Generalization in Multimodal First-Person Action Recognition—0
Deep Bilinear Learning for RGB-D Action Recognition—0
A Survey on Multimodal Wearable Sensor-based Human Action Recognition—0
Lattice Long Short-Term Memory for Human Action Recognition—0
A Survey on Human Action Recognition—0
A Survey on Contrastive Self-supervised Learning—0
Deep Alternative Neural Network: Exploring Contexts as Early as Possible for Action Recognition—0
Deep-Aligned Convolutional Neural Network for Skeleton-based Action Recognition and Segmentation—0
Modular Action Concept Grounding in Semantic Video Prediction—0
DeepActsNet: Spatial and Motion features from Face, Hands, and Body Combined with Convolutional and Graph Networks for Improved Action Recognition—0
Deep Action- and Context-Aware Sequence Learning for Activity Recognition and Anticipation—0
A Survey on Backbones for Deep Video Action Recognition—0
Independent Sign Language Recognition with 3D Body, Hands, and Face Reconstruction—0
Including Semantic Information via Word Embeddings for Skeleton-based Action Recognition—0
A Survey on 3D Skeleton-Based Action Recognition Using Learning Method—0
Actor-Centric Relation Network—0
LS-HAR: Language Supervised Human Action Recognition with Salient Fusion, Construction Sites as a Use-Case—0
A Survey of Visual Analysis of Human Motion and Its Applications—0
Improving the Multi-label Atomic Activity Recognition by Robust Visual Feature and Advanced Attention @ ROAD++ Atomic Activity Recognition 2024—0
Accelerating temporal action proposal generation via high performance computing—0
Decision Support for Video-based Detection of Flu Symptoms—0
Language-based Action Concept Spaces Improve Video Self-Supervised Learning—0
Deception Detection in Videos—0
Improving Skeleton-based Action Recognitionwith Robust Spatial and Temporal Features—0
3D R Transform on Spatio-temporal Interest Points for Action Recognition—0
Improving performance of recurrent neural network with relu nonlinearity—0
Decoupled Prompt-Adapter Tuning for Continual Activity Recognition—0
Improving Video Violence Recognition with Human Interaction Learning on 3D Skeleton Point Clouds—0
A Survey of Video-based Action Quality Assessment—0
Incremental Deep Learning for Robust Object Detection in Unknown Cluttered Environments—0
Language as the Medium: Multimodal Video Classification through text only—0
IndGIC: Supervised Action Recognition under Low Illumination—0
Inductive Attention for Video Action Anticipation—0
Improving Interpretability of Deep Neural Networks with Semantic Information—0
Inertial Sensor Data To Image Encoding For Human Action Recognition—0
Inferring Temporal Compositions of Actions Using Probabilistic Automata—0
Improving Human Action Recognition by Non-action Classification—0
DDLSTM: Dual-Domain LSTM for Cross-Dataset Action Recognition—0
Information Elevation Network for Fast Online Action Detection—0
Informed Democracy: Voting-based Novelty Detection for Action Recognition—0
Improving Zero-Shot Action Recognition using Human Instruction with Text Description—0
A Survey of IMU Based Cross-Modal Transfer Learning in Human Activity Recognition—0
Action Concept Grounding Network for Semantically-Consistent Video Generation—0
InsTALL: Context-aware Instructional Task Assistance with Multi-modal Large Language Models—0
Improved Dense Trajectory with Cross Streams—0
DAVE: Diverse Atomic Visual Elements Dataset with High Representation of Vulnerable Road Users in Complex and Unpredictable Environments—0
A Study On the Effects of Pre-processing On Spatio-temporal Action Recognition Using Spiking Neural Networks Trained with STDP—0
2D or not 2D? Adaptive 3D Convolution Selection for Efficient Video Recognition—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
4InternVideoTop-1 Accuracy77.2—Unverified
5DejaVidTop-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
3OmniVec3-fold Accuracy99.6—Unverified
4VideoMAE V2-g3-fold Accuracy99.6—Unverified
5BIKE3-fold Accuracy98.8—Unverified
6SMART3-fold Accuracy98.64—Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6—Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6—Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6—Unverified
10Text4Vis3-fold Accuracy98.2—Unverified