61 citations · 76 across the 5 of their papers we have counts for
5 papers · 1 filter
UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation
Jianghao Wu, Guotai Wang, Ran Gu +6
Domain Adaptation (DA) is important for deep learning-based medical image segmentation models to deal with testing images from a new target domain. As the source-domain data are us…
SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos
Haisong Liu, Yao Teng, Tao Lu +2
Camera-based 3D object detection in BEV (Bird's Eye View) space has drawn great attention over the past few years. Dense detectors typically follow a two-stage pipeline by first co…
UM-CAM: Uncertainty-weighted Multi-resolution Class Activation Maps for Weakly-supervised Fetal Brain Segmentation
Jia Fu, Tao Lu, Shaoting Zhang +1
Accurate segmentation of the fetal brain from Magnetic Resonance Image (MRI) is important for prenatal assessment of fetal development. Although deep learning has shown the potenti…
LinK: Linear Kernel for LiDAR-based 3D Perception
Tao Lu, Xiang Ding, Haisong Liu +2
Extending the success of 2D Large Kernel to 3D perception is challenging due to: 1. the cubically-increasing overhead in processing 3D data; 2. the optimization difficulties from d…
Learning Optical Flow and Scene Flow with Bidirectional Camera-LiDAR Fusion
Haisong Liu, Tao Lu, Yihui Xu +2
In this paper, we study the problem of jointly estimating the optical flow and scene flow from synchronized 2D and 3D data. Previous methods either employ a complex pipeline that s…