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 751775 of 2759 papers

TitleStatusHype
BiaSwap: Removing dataset bias with bias-tailored swapping augmentation0
Activation-wise Propagation: A Universal Strategy to Break Timestep Constraints in Spiking Neural Networks for 3D Data Processing0
A Hierarchical Context Model for Event Recognition in Surveillance Video0
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks0
3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition0
Exploring Relations in Untrimmed Videos for Self-Supervised Learning0
A Grid-based Representation for Human Action Recognition0
Beyond the Pixels: Exploring the Effects of Bit-Level Network and File Corruptions on Video Model Robustness0
Exploiting Structure Sparsity for Covariance-based Visual Representation0
Beyond the Camera: Neural Networks in World Coordinates0
A Generative Restricted Boltzmann Machine Based Method for High-Dimensional Motion Data Modeling0
Action Recognition Based on Joint Trajectory Maps with Convolutional Neural Networks0
Exploiting the ConvLSTM: Human Action Recognition using Raw Depth Video-Based Recurrent Neural Networks0
Beyond Spatial Pyramid Matching: Space-time Extended Descriptor for Action Recognition0
A Generative Approach to Zero-Shot and Few-Shot Action Recognition0
A Baseline Framework for Part-level Action Parsing and Action Recognition0
Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories0
Beyond Image Classification: A Video Benchmark and Dual-Branch Hybrid Discrimination Framework for Compositional Zero-Shot Learning0
A baseline on continual learning methods for video action recognition0
Exploiting Spatial-Temporal Modelling and Multi-Modal Fusion for Human Action Recognition0
Beyond Gaussian Pyramid: Multi-skip Feature Stacking for Action Recognition0
Beyond Covariance: Feature Representation With Nonlinear Kernel Matrices0
A Fine-to-Coarse Convolutional Neural Network for 3D Human Action Recognition0
Better Exploiting Motion for Better Action Recognition0
AFE-CNN: 3D Skeleton-based Action Recognition with Action Feature Enhancement0
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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