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cs.CV2023
Single-stage Multi-human Parsing via Point Sets and Center-based Offsets
Jiaming Chu, Lei Jin, Junliang Xing +1
This work studies the multi-human parsing problem. Existing methods, either following top-down or bottom-up two-stage paradigms, usually involve expensive computational costs. We i…
cs.CV2022★ 1 cited
AdaptivePose++: A Powerful Single-Stage Network for Multi-Person Pose Regression
Yabo Xiao, Xiaojuan Wang, Dongdong Yu +5
Multi-person pose estimation generally follows top-down and bottom-up paradigms. Both of them use an extra stage ( human detection in top-down paradigm or group…
cs.CV2022
Learning Quality-aware Representation for Multi-person Pose Regression
Yabo Xiao, Dongdong Yu, Xiaojuan Wang +3
Off-the-shelf single-stage multi-person pose regression methods generally leverage the instance score (i.e., confidence of the instance localization) to indicate the pose quality f…