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 23262350 of 2759 papers

TitleStatusHype
Multimodal Visual Concept Learning with Weakly Supervised TechniquesCode0
Analyzing Human-Human Interactions: A SurveyCode0
Multi-Moments in Time: Learning and Interpreting Models for Multi-Action Video UnderstandingCode0
Multiple Human Tracking using Multi-Cues including Primitive Action FeaturesCode0
Contextualized Spatio-Temporal Contrastive Learning with Self-SupervisionCode0
FPGA-QHAR: Throughput-Optimized for Quantized Human Action Recognition on The EdgeCode0
FAR: Fourier Aerial Video RecognitionCode0
Contextual Explainable Video Representation: Human Perception-based UnderstandingCode0
Multi-scale spatial–temporal convolutional neural network for skeleton-based action recognitionCode0
MMTM: Multimodal Transfer Module for CNN FusionCode0
Fourier Analysis on Robustness of Graph Convolutional Neural Networks for Skeleton-based Action RecognitionCode0
Flow Snapshot Neurons in Action: Deep Neural Networks Generalize to Biological Motion PerceptionCode0
MMG-Ego4D: Multimodal Generalization in Egocentric Action RecognitionCode0
MMG-Ego4D: Multi-Modal Generalization in Egocentric Action RecognitionCode0
MultiSensor-Home: A Wide-area Multi-modal Multi-view Dataset for Action Recognition and Transformer-based Sensor FusionCode0
FLAG3D: A 3D Fitness Activity Dataset with Language InstructionCode0
Temporal Relational Reasoning in VideosCode0
Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action RecognitionCode0
Temporal Relations of Informative Frames in Action RecognitionCode0
Simple yet efficient real-time pose-based action recognitionCode0
Simplifying Open-Set Video Domain Adaptation with Contrastive LearningCode0
Assembly101: A Large-Scale Multi-View Video Dataset for Understanding Procedural ActivitiesCode0
Temporal Residual Networks for Dynamic Scene RecognitionCode0
MLP-3D: A MLP-like 3D Architecture with Grouped Time MixingCode0
Vision-Language Meets the Skeleton: Progressively Distillation with Cross-Modal Knowledge for 3D Action Representation LearningCode0
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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