Papers with Code 아카이브
Multi-Person Pose Estimation and Tracking
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Joint multi-person pose estimation and tracking following the PoseTrack benchmark. https://posetrack.net/
<span style="color:grey; opacity: 0.6">( Image credit: PoseTrack )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
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
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking
Self-supervised Keypoint Correspondences for Multi-Person Pose Estimation and Tracking in Videos
FastPose: Towards Real-time Pose Estimation and Tracking via Scale-normalized Multi-task Networks
Multi-person Articulated Tracking with Spatial and Temporal Embeddings
Multi-Domain Pose Network for Multi-Person Pose Estimation and Tracking
Learning to Refine Human Pose Estimation
PoseTrack: Joint Multi-Person Pose Estimation and Tracking
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.