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 24762500 of 2759 papers

TitleStatusHype
Human Action Recognition using Local Two-Stream Convolution Neural Network Features and Support Vector Machines0
Human action recognition with a large-scale brain-inspired photonic computer0
Human Action Recognition with Deep Temporal Pyramids0
Human Action Recognition with Multi-Laplacian Graph Convolutional Networks0
Human Action Recognition without Human0
Human Activity Recognition Using Cascaded Dual Attention CNN and Bi-Directional GRU Framework0
Human activity recognition using deep learning approaches and single frame cnn and convolutional lstm0
Human activity recognition using improved dynamic image0
Human and Machine Action Prediction Independent of Object Information0
Human-Centered Prior-Guided and Task-Dependent Multi-Task Representation Learning for Action Recognition Pre-Training0
Human-Centric Transformer for Domain Adaptive Action Recognition0
Human in Events: A Large-Scale Benchmark for Human-centric Video Analysis in Complex Events0
Human Pose-based Estimation, Tracking and Action Recognition with Deep Learning: A Survey0
Human Stone Toolmaking Action Grammar (HSTAG): A Challenging Benchmark for Fine-grained Motor Behavior Recognition0
HumanVBench: Exploring Human-Centric Video Understanding Capabilities of MLLMs with Synthetic Benchmark Data0
HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling0
HumMUSS: Human Motion Understanding using State Space Models0
HyLiFormer: Hyperbolic Linear Attention for Skeleton-based Human Action Recognition0
Hyper-Fisher Vectors for Action Recognition0
Hypergraph-based Multi-View Action Recognition using Event Cameras0
iCub! Do you recognize what I am doing?: multimodal human action recognition on multisensory-enabled iCub robot0
Identifying Auxiliary or Adversarial Tasks Using Necessary Condition Analysis for Adversarial Multi-task Video Understanding0
Identity-free Artificial Emotional Intelligence via Micro-Gesture Understanding0
IF-TTN: Information Fused Temporal Transformation Network for Video Action Recognition0
IIP-Transformer: Intra-Inter-Part Transformer for Skeleton-Based Action Recognition0
Show:102550
← PrevPage 100 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