Papers with Code 아카이브
Multi-Person Pose Estimation
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Multi-person pose estimation is the task of estimating the pose of multiple people in one frame.
<span style="color:grey; opacity: 0.6">( Image credit: Human Pose Estimation with TensorFlow )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
DETRPose: Real-time end-to-end transformer model for multi-person pose estimation
LGM-Pose: A Lightweight Global Modeling Network for Real-time Human Pose Estimation
MultiFormer: A Multi-Person Pose Estimation System Based on CSI and Attention Mechanism
Multi-person Physics-based Pose Estimation for Combat Sports
RapidPoseTriangulation: Multi-view Multi-person Whole-body Human Pose Triangulation in a Millisecond
SimpleDepthPose: Fast and Reliable Human Pose Estimation with RGBD-Images
Poseidon: A ViT-based Architecture for Multi-Frame Pose Estimation with Adaptive Frame Weighting and Multi-Scale Feature Fusion
Waterfall Transformer for Multi-person Pose Estimation
VoxelKeypointFusion: Generalizable Multi-View Multi-Person Pose Estimation
DHRNet: A Dual-Path Hierarchical Relation Network for Multi-Person Pose Estimation
DRSI-Net: Dual-Residual Spatial Interaction Network for Multi-Person Pose Estimation
RTMO: Towards High-Performance One-Stage Real-Time Multi-Person Pose Estimation
Human Pose-based Estimation, Tracking and Action Recognition with Deep Learning: A Survey
X-Pose: Detecting Any Keypoints
Denoising and Selecting Pseudo-Heatmaps for Semi-Supervised Human Pose Estimation
BoIR: Box-Supervised Instance Representation for Multi-Person Pose Estimation
Towards Robust and Smooth 3D Multi-Person Pose Estimation from Monocular Videos in the Wild
Group Pose: A Simple Baseline for End-to-End Multi-person Pose Estimation
LAMP: Leveraging Language Prompts for Multi-person Pose Estimation
Joint Coordinate Regression and Association For Multi-Person Pose Estimation, A Pure Neural Network Approach
Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguity
A Feasibility Study on Indoor Localization and Multi-person Tracking Using Sparsely Distributed Camera Network with Edge Computing
Hybrid model for Single-Stage Multi-Person Pose Estimation
Global Relation Modeling and Refinement for Bottom-Up Human Pose Estimation
RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose
Texture-Based Input Feature Selection for Action Recognition
MDPose: Real-Time Multi-Person Pose Estimation via Mixture Density Model
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art History
Weakly Supervised 3D Multi-person Pose Estimation for Large-scale Scenes based on Monocular Camera and Single LiDAR
AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time
JRDB-Pose: A Large-scale Dataset for Multi-Person Pose Estimation and Tracking
AdaptivePose++: A Powerful Single-Stage Network for Multi-Person Pose Regression
QuickPose: Real-time Multi-view Multi-person Pose Estimation in Crowded Scenes
Mutual Adaptive Reasoning for Monocular 3D Multi-Person Pose Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.