136 citations · 321 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
PP-PicoDet: A Better Real-Time Object Detector on Mobile Devices
Guanghua Yu, Qinyao Chang, Wenyu Lv +12
The better accuracy and efficiency trade-off has been a challenging problem in object detection. In this work, we are dedicated to studying key optimizations and neural network arc…
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…
PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation
Yi Liu, Lutao Chu, Guowei Chen +4
Image Segmentation plays an essential role in computer vision and image processing with various applications from medical diagnosis to autonomous car driving. A lot of segmentation…