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2D Human Pose Estimation

369 평가 기록 50 datasets

What is Human Pose Estimation? Human pose estimation is the process of estimating the configuration of the body (pose) from a single, typically monocular, image. Background. Human pose estimation is one of the key problems in computer vision that has been studied for well over 15 years. The reason for its importance is the abundance of applications that can benefit from such a technology. For example, human pose estimation allows for higher-level reasoning in the context of human-computer interaction and activity recognition; it is also one of the basic building blocks for marker-less motion capture (MoCap) technology. MoCap technology is useful for applications ranging from character animation to clinical analysis of gait pathologies.

개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.

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Dataset기록된 모델 예시MetricPaperCode
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
BSRGAN
PSNR: 29.27LPIPS: 0.177SSIM: 0.836
논문 코드
VRT
Subjective score: 7.628ERQAv1.0: 0.758QRCRv1.0: 0.722SSIM: 0.902
논문 코드
EvTexture+
PSNR: 29.78SSIM: 0.8983
논문 코드
RVRT
PSNR: 29.54SSIM: 0.8810
논문 코드
RTMW-x
WB: 70.2body: 76.3foot: 79.6face: 88.4
논문 코드
BBox-Mask-Pose 2x
Test AP: 48.3Validation AP: 48.6
논문 코드
UniPose
AP: 0.759
논문 코드
PlausiVL
Recall@5: 27.60Top-5 Verb: 55.62Top-5 Noun: 54.23
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InAViT
recall@5: 23.75
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Abstract Goal
Top 1 Accuracy - Verb: 35.34Top 1 Accuracy - Noun: 51.56Top 1 Accuracy - Act.: 22.03Top 5 Accuracy - Verb: 82.56
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Abstract Goal
Top 1 Accuracy - Verb: 41.41Top 1 Accuracy - Noun: 22.36Top 1 Accuracy - Act.: 13.28Top 5 Accuracy - Verb: 73.10
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