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Keypoint Detection

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하위 태스크
0
평가표
9
보존된 평가 기록
83

Keypoint Detection is essential for analyzing and interpreting images in computer vision. It involves simultaneously detecting and localizing interesting points in an image. Keypoints, also known as interest points, are spatial locations or points in the image that define what is interesting or what stands out. They are invariant to image rotation, shrinkage, translation, distortion, etc. Keypoints examples are body joints, facial landmarks, or any other salient points in objects. Keypoints have uses in problems such as pose estimation, object detection and tracking, facial analysis, and augmented reality.

<span style="color:grey; opacity: 0.6">( Image credit: PifPaf: Composite Fields for Human Pose Estimation; "Learning to surf" by fotologic, license: CC-BY-2.0 )</span>

평가 결과

데이터셋과 평가 조건을 선택해 성능·논문·코드를 비교하세요. 보존된 Papers with Code 기록으로, 최신 순위는 아닙니다.

COCO test-dev

원본 태스크: 1 Image, 2*2 Stitchi / Pose Estimation / Keypoint Detection

평가 기록 16건

OCHuman

원본 태스크: 1 Image, 2*2 Stitchi / Pose Estimation / Keypoint Detection

평가 기록 10건

MPII Multi-Person

원본 태스크: 1 Image, 2*2 Stitchi / Pose Estimation / Keypoint Detection

평가 기록 9건

ViCoS Towel Dataset

원본 태스크: 1 Image, 2*2 Stitchi / Pose Estimation / Keypoint Detection

평가 기록 9건

COCO test-challenge

원본 태스크: 1 Image, 2*2 Stitchi / Pose Estimation / Keypoint Detection

평가 기록 8건

Pascal3D+

원본 태스크: 1 Image, 2*2 Stitchi / Pose Estimation / Keypoint Detection

평가 기록 4건

COCO

원본 태스크: 1 Image, 2*2 Stitchi / Pose Estimation / Keypoint Detection

평가 기록 2건

ApolloCar3D

원본 태스크: 1 Image, 2*2 Stitchi / Pose Estimation / Keypoint Detection

평가 기록 1건

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