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 676700 of 2759 papers

TitleStatusHype
Action Recognition Based on Optimal Joint Selection and Discriminative Depth DescriptorCode0
MMG-Ego4D: Multimodal Generalization in Egocentric Action RecognitionCode0
Mining YouTube - A dataset for learning fine-grained action concepts from webly supervised video dataCode0
MFAS: Multimodal Fusion Architecture SearchCode0
REPAIR: Removing Representation Bias by Dataset ResamplingCode0
Mission Balance: Generating Under-represented Class Samples using Video Diffusion ModelsCode0
MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation LearningCode0
Beyond the Self: Using Grounded Affordances to Interpret and Describe Others' ActionsCode0
MD-BERT: Action Recognition in Dark Videos via Dynamic Multi-Stream Fusion and Temporal ModelingCode0
Beyond the Benchmark: Detecting Diverse Anomalies in VideosCode0
Memory Attention Networks for Skeleton-based Action RecognitionCode0
Meta-path Analysis on Spatio-Temporal Graphs for Pedestrian Trajectory PredictionCode0
Action Recognition based on Cross-Situational Action-object StatisticsCode0
Beyond Short Snippets: Deep Networks for Video ClassificationCode0
AGAR: Attention Graph-RNN for Adaptative Motion Prediction of Point Clouds of Deformable ObjectsCode0
MetaVD: A Meta Video Dataset for enhancing human action recognition datasetsCode0
MARINE: A Computer Vision Model for Detecting Rare Predator-Prey Interactions in Animal VideosCode0
MARS: Motion-Augmented RGB Stream for Action RecognitionCode0
Mamba Fusion: Learning Actions Through QuestioningCode0
Mask and Compress: Efficient Skeleton-based Action Recognition in Continual LearningCode0
AENet: Learning Deep Audio Features for Video AnalysisCode0
Making Third Person Techniques Recognize First-Person Actions in Egocentric VideosCode0
Long-term Temporal Convolutions for Action RecognitionCode0
Low-light Environment Neural SurveillanceCode0
Bayesian Hierarchical Dynamic Model for Human Action RecognitionCode0
Show:102550
← PrevPage 28 of 111Next →

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