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 11511175 of 2759 papers

TitleStatusHype
Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures0
Interpretable Spatio-temporal Attention for Video Action Recognition0
In the Eye of the Beholder: Gaze and Actions in First Person Video0
Deep-Temporal LSTM for Daily Living Action Recognition0
Deep Spatio-temporal Manifold Network for Action Recognition0
Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition0
Deep set conditioned latent representations for action recognition0
ActionFlowNet: Learning Motion Representation for Action Recognition0
Deep Sequential Context Networks for Action Prediction0
Adapting Vision-Language Models for Evaluating World Models0
3D Skeleton-based Few-shot Action Recognition with JEANIE is not so Naïve0
Deep Quantization: Encoding Convolutional Activations with Deep Generative Model0
Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition0
Attend and Interact: Higher-Order Object Interactions for Video Understanding0
InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation0
Action Detection by Implicit Intentional Motion Clustering0
Deep Neural Networks in Video Human Action Recognition: A Review0
2D versus 3D Convolutional Spiking Neural Networks Trained with Unsupervised STDP for Human Action Recognition0
Deep Multimodal Feature Analysis for Action Recognition in RGB+D Videos0
Deep Multi-Kernel Convolutional LSTM Networks and an Attention-Based Mechanism for Videos0
Deep Motion Features for Visual Tracking0
ATTACH Dataset: Annotated Two-Handed Assembly Actions for Human Action Understanding0
Deep manifold-to-manifold transforming network for action recognition0
Deep Local Video Feature for Action Recognition0
A Training Method For VideoPose3D With Ideology of Action Recognition0
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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