AP: 76.5
Papers with Code · CC BY-SA 4.0
Pose Estimation
Pose Estimation is a computer vision task where the goal is to detect the position and orientation of a person or an object. Usually, this is done by predicting the location of specific keypoints like hands, head, elbows, etc. in case of Human Pose Estimation.
A common benchmark for this task is MPII Human Pose
<span style="color:grey; opacity: 0.6">( Image credit: Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose )</span>
개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.
벤치마크
Papers with Code 아카이브의 데이터셋별 기록 예시입니다. 평가 조건과 지표 방향이 검증되지 않아 순위를 의미하지 않습니다.
Dataset기록된 모델 예시MetricPaperCode
LMT R152 384x384
Average MPJPE (mm): 17.59Using 2D ground-truth joints: NoMulti-View or Monocular: Multi-ViewMPVE (mm): 23.7
논문
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RealSR + x264
BSQ-rate over ERQA: 0.77BSQ-rate over Subjective Score: 0.196BSQ-rate over VMAF: 0.775BSQ-rate over PSNR: 0.675
논문
코드
MotionBERT (Finetune)
Average MPJPE (mm): 37.5Use Video Sequence: YesFrames Needed: 243Need Ground Truth 2D Pose: No
논문
코드
AdaptPose
Average MPJPE (mm): 42.5Number of Views: 1Number of Frames Per View: 273D Annotations: S1
논문
코드
데이터셋
213개논문
MAE yaw (º): 1.62MAE pitch (º): 1.80MAE roll (º): 1.24
Mean PCK@0.2: 91.9
Mean PCK@0.2: 99.0Mean PCK@0.1: 94.6Mean PCK@0.05: 80.6
Mean PCK@0.2: 80.5Mean PCK@0.1: 58.3
Mean PCK@0.2: 99.6Mean PCK@0.1: 98.3Mean PCK@0.05: 91.9
Mean PCK@0.2: 93.6
MAE mean (º): 1.56
0..5sec: Jaau
MAE mean (º): 1.29MAE yaw (º): 1.41MAE pitch (º): 1.70MAE roll (º): 0.77
Test AP: 93.3Validation AP: 92.8
라이브러리
Papers with Code 리더보드 row에 연결된 구현 저장소입니다.
하위 태스크
3H
3D Human Pose Estimation
HP
Hand Pose Estimation
MP
Multi-Person Pose Estimation
KD
Keypoint Detection
HP
Head Pose Estimation
HP
Human Pose Forecasting
6P
6D Pose Estimation
6P
6D Pose Estimation using RGB
AP
Animal Pose Estimation
6P
6D Pose Estimation using RGBD
VP
Vehicle Pose Estimation
3P
3D Pose Estimation