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 601625 of 2759 papers

TitleStatusHype
Language-based Action Concept Spaces Improve Video Self-Supervised Learning0
Actor-agnostic Multi-label Action Recognition with Multi-modal QueryCode1
AGAR: Attention Graph-RNN for Adaptative Motion Prediction of Point Clouds of Deformable ObjectsCode0
What Can Simple Arithmetic Operations Do for Temporal Modeling?Code1
Fusing Hand and Body Skeletons for Human Action Recognition in Assembly0
Measuring Student Behavioral Engagement using Histogram of Actions0
Human Action Recognition in Still Images Using ConViT0
Similarity Min-Max: Zero-Shot Day-Night Domain Adaptation0
SkeletonMAE: Graph-based Masked Autoencoder for Skeleton Sequence Pre-trainingCode1
Integrating Human Parsing and Pose Network for Human Action RecognitionCode1
Cross-Model Cross-Stream Learning for Self-Supervised Human Action RecognitionCode0
SoccerKDNet: A Knowledge Distillation Framework for Action Recognition in Soccer Videos0
Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action RecognitionCode1
One-Shot Action Recognition via Multi-Scale Spatial-Temporal Skeleton Matching0
Multimodal Distillation for Egocentric Action RecognitionCode1
Video-FocalNets: Spatio-Temporal Focal Modulation for Video Action RecognitionCode1
A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 20230
InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation0
Free-Form Composition Networks for Egocentric Action Recognition0
EgoVLPv2: Egocentric Video-Language Pre-training with Fusion in the BackboneCode1
EgoAdapt: A multi-stream evaluation study of adaptation to real-world egocentric user videoCode1
HA-ViD: A Human Assembly Video Dataset for Comprehensive Assembly Knowledge UnderstandingCode0
Fine-grained Action Analysis: A Multi-modality and Multi-task Dataset of Figure SkatingCode0
VideoGLUE: Video General Understanding Evaluation of Foundation Models0
Make A Long Image Short: Adaptive Token Length for Vision Transformers0
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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