activity
20202022
most citedBoosting Semantic Human Matting with Coarse Annotations

9 citations · 17 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20228 cited

Box2Mask: Box-supervised Instance Segmentation via Level-set Evolution

Wentong Li, Wenyu Liu, Jianke Zhu +4

In contrast to fully supervised methods using pixel-wise mask labels, box-supervised instance segmentation takes advantage of simple box annotations, which has recently attracted i…

cs.CV2022

Structure-Aware Flow Generation for Human Body Reshaping

Jianqiang Ren, Yuan Yao, Biwen Lei +2

Body reshaping is an important procedure in portrait photo retouching. Due to the complicated structure and multifarious appearance of human bodies, existing methods either fall ba…

cs.CV2021

PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency

Jie Liang, Hui Zeng, Miaomiao Cui +2

Different from general photo retouching tasks, portrait photo retouching (PPR), which aims to enhance the visual quality of a collection of flat-looking portrait photos, has its sp…

cs.CV2021

Attention-guided Temporally Coherent Video Object Matting

Yunke Zhang, Chi Wang, Miaomiao Cui +6

This paper proposes a novel deep learning-based video object matting method that can achieve temporally coherent matting results. Its key component is an attention-based temporal a…

cs.CV20209 cited

Boosting Semantic Human Matting with Coarse Annotations

Jinlin Liu, Yuan Yao, Wendi Hou +4

Semantic human matting aims to estimate the per-pixel opacity of the foreground human regions. It is quite challenging and usually requires user interactive trimaps and plenty of h…