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 22762300 of 2759 papers

TitleStatusHype
Evolving Skeletons: Motion Dynamics in Action Recognition0
Evolving Space-Time Neural Architectures for Videos0
Examining Interpretable Feature Relationships in Deep Networks for Action recognition0
EXMOVES: Classifier-based Features for Scalable Action Recognition0
Egocentric and Exocentric Methods: A Short Survey0
Expanded Parts Model for Human Attribute and Action Recognition in Still Images0
Expansion-Squeeze-Excitation Fusion Network for Elderly Activity Recognition0
Exploiting deep residual networks for human action recognition from skeletal data0
Exploiting Inter-Frame Regional Correlation for Efficient Action Recognition0
Exploiting Motion Information from Unlabeled Videos for Static Image Action Recognition0
Exploiting Spatial-Temporal Modelling and Multi-Modal Fusion for Human Action Recognition0
Exploiting Structure Sparsity for Covariance-based Visual Representation0
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks0
Exploring AI-based Anonymization of Industrial Image and Video Data in the Context of Feature Preservation0
Exploring Explainability in Video Action Recognition0
Exploring Missing Modality in Multimodal Egocentric Datasets0
Exploring Relations in Untrimmed Videos for Self-Supervised Learning0
Exploring Sub-Pseudo Labels for Learning from Weakly-Labeled Web Videos0
Exploring the Impact of Hand Pose and Shadow on Hand-washing Action Recognition0
Extended multi-stream temporal-attention module for skeleton-based human action recognition (HAR)0
Extending Temporal Data Augmentation for Video Action Recognition0
Extensible Hierarchical Method of Detecting Interactive Actions for Video Understanding0
Leveraging Endo- and Exo-Temporal Regularization for Black-box Video Domain Adaptation0
Extrinsic Methods for Coding and Dictionary Learning on Grassmann Manifolds0
F4D: Factorized 4D Convolutional Neural Network for Efficient Video-level Representation Learning0
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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
4InternVideoTop-1 Accuracy77.2Unverified
5DejaVidTop-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
3OmniVec3-fold Accuracy99.6Unverified
4VideoMAE V2-g3-fold Accuracy99.6Unverified
5BIKE3-fold Accuracy98.8Unverified
6SMART3-fold Accuracy98.64Unverified
7ZeroI2V ViT-L/143-fold Accuracy98.6Unverified
8OmniSource (SlowOnly-8x8-R101-RGB + I3D-Flow)3-fold Accuracy98.6Unverified
9PERF-Net (multi-distilled S3D)3-fold Accuracy98.6Unverified
10Text4Vis3-fold Accuracy98.2Unverified