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
REACT: Recognize Every Action Everywhere All At Once0
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding0
Real Time Action Recognition from Video Footage0
Real-time Action Recognition with Dissimilarity-based Training of Specialized Module Networks0
Real-time Action Recognition with Enhanced Motion Vector CNNs0
Real-Time Driver State Monitoring Using a CNN Based Spatio-Temporal Approach0
Real-Time Elderly Monitoring for Senior Safety by Lightweight Human Action Recognition0
Real-Time End-to-End Action Detection with Two-Stream Networks0
Real-Time Human Action Recognition on Embedded Platforms0
Real-time Human Action Recognition Using Locally Aggregated Kinematic-Guided Skeletonlet and Supervised Hashing-by-Analysis Model0
Real-time Human Pose Estimation from Video with Convolutional Neural Networks0
MorphMLP: An Efficient MLP-Like Backbone for Spatial-Temporal Representation LearningCode0
ADG-Pose: Automated Dataset Generation for Real-World Human Pose EstimationCode0
Adaptive frame selection in two dimensional convolutional neural network action recognitionCode0
UAV-GESTURE: A Dataset for UAV Control and Gesture RecognitionCode0
Multi-attention Networks for Temporal Localization of Video-level LabelsCode0
Asynchronous Temporal Fields for Action RecognitionCode0
Multi class activity classification in videos using Motion History Image generationCode0
More Is Less: Learning Efficient Video Representations by Big-Little Network and Depthwise Temporal AggregationCode0
Asymmetric Masked Distillation for Pre-Training Small Foundation ModelsCode0
UCF101: A Dataset of 101 Human Actions Classes From Videos in The WildCode0
Gate-Shift-Pose: Enhancing Action Recognition in Sports with Skeleton InformationCode0
Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action RecognitionCode0
A Bag-of-Words Equivalent Recurrent Neural Network for Action RecognitionCode0
Gate-Shift Networks for Video Action RecognitionCode0
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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