most citedPP-LiteSeg: A Superior Real-Time Semantic Segmentation Model

136 citations · 203 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV20221 cited

RAIS: Robust and Accurate Interactive Segmentation via Continual Learning

Yuying Hao, Yi Liu, Juncai Peng +5

Interactive image segmentation aims at segmenting a target region through a way of human-computer interaction. Recent works based on deep learning have achieved excellent performan…

cs.CV202225 cited

EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle

Yuying Hao, Yi Liu, Yizhou Chen +7

In recent years, the rapid development of deep learning has brought great advancements to image and video segmentation methods based on neural networks. However, to unleash the ful…

cs.CV202217 cited

PP-Matting: High-Accuracy Natural Image Matting

Guowei Chen, Yi Liu, Jian Wang +11

Natural image matting is a fundamental and challenging computer vision task. It has many applications in image editing and composition. Recently, deep learning-based approaches hav…

cs.CV2022136 cited

PP-LiteSeg: A Superior Real-Time Semantic Segmentation Model

Juncai Peng, Yi Liu, Shiyu Tang +13

Real-world applications have high demands for semantic segmentation methods. Although semantic segmentation has made remarkable leap-forwards with deep learning, the performance of…

cs.CV20216 cited

EdgeFlow: Achieving Practical Interactive Segmentation with Edge-Guided Flow

Yuying Hao, Yi Liu, Zewu Wu +8

High-quality training data play a key role in image segmentation tasks. Usually, pixel-level annotations are expensive, laborious and time-consuming for the large volume of trainin…

cs.CV20215 cited

Unsupervised domain adaptation via coarse-to-fine feature alignment method using contrastive learning

Shiyu Tang, Peijun Tang, Yanxiang Gong +2

Previous feature alignment methods in Unsupervised domain adaptation(UDA) mostly only align global features without considering the mismatch between class-wise features. In this wo…