30 citations · 65 across the 9 of their papers we have counts for
15 papers
A Compacted Structure for Cross-domain learning on Monocular Depth and Flow Estimation
Yu Chen, Xu Cao, Xiaoyi Lin +4
Accurate motion and depth recovery is important for many robot vision tasks including autonomous driving. Most previous studies have achieved cooperative multi-task interaction via…
Self-Supervised Depth Estimation in Laparoscopic Image using 3D Geometric Consistency
Baoru Huang, Jian-Qing Zheng, Anh Nguyen +6
Depth estimation is a crucial step for image-guided intervention in robotic surgery and laparoscopic imaging system. Since per-pixel depth ground truth is difficult to acquire for…
When CNN Meet with ViT: Towards Semi-Supervised Learning for Multi-Class Medical Image Semantic Segmentation
Ziyang Wang, Tianze Li, Jian-Qing Zheng +1
Due to the lack of quality annotation in medical imaging community, semi-supervised learning methods are highly valued in image semantic segmentation tasks. In this paper, an advan…
Recursive Deformable Image Registration Network with Mutual Attention
Jian-Qing Zheng, Ziyang Wang, Baoru Huang +3
Deformable image registration, estimating the spatial transformation between different images, is an important task in medical imaging. Many previous studies have used learning-bas…
Residual Aligner Network
Jian-Qing Zheng, Ziyang Wang, Baoru Huang +2
Image registration is important for medical imaging, the estimation of the spatial transformation between different images. Many previous studies have used learning-based methods f…
Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images
Baoru Huang, Jianqing Zheng, Anh Nguyen +4
Dense depth estimation and 3D reconstruction of a surgical scene are crucial steps in computer assisted surgery. Recent work has shown that depth estimation from a stereo images pa…