49 citations · 90 across the 14 of their papers we have counts for
14 papers
DDFP: Data-dependent Frequency Prompt for Source Free Domain Adaptation of Medical Image Segmentation
Siqi Yin, Shaolei Liu, Manning Wang
Domain adaptation addresses the challenge of model performance degradation caused by domain gaps. In the typical setup for unsupervised domain adaptation, labeled data from a sourc…
Weakly Semi-supervised Whole Slide Image Classification by Two-level Cross Consistency Supervision
Linhao Qu, Shiman Li, Xiaoyuan Luo +4
Computer-aided Whole Slide Image (WSI) classification has the potential to enhance the accuracy and efficiency of clinical pathological diagnosis. It is commonly formulated as a Mu…
SP : Superpixel-propagated pseudo-label learning for weakly semi-supervised medical image segmentation
Shiman Li, Jiayue Zhao, Shaolei Liu +3
Deep learning-based medical image segmentation helps assist diagnosis and accelerate the treatment process while the model training usually requires large-scale dense annotation da…
Local Implicit Wavelet Transformer for Arbitrary-Scale Super-Resolution
Minghong Duan, Linhao Qu, Shaolei Liu +1
Implicit neural representations have recently demonstrated promising potential in arbitrary-scale Super-Resolution (SR) of images. Most existing methods predict the pixel in the SR…
Reducing Domain Gap in Frequency and Spatial domain for Cross-modality Domain Adaptation on Medical Image Segmentation
Shaolei Liu, Siqi Yin, Linhao Qu +1
Unsupervised domain adaptation (UDA) aims to learn a model trained on source domain and performs well on unlabeled target domain. In medical image segmentation field, most existing…
Robust Point Cloud Registration Framework Based on Deep Graph Matching(TPAMI Version)
Kexue Fu, Jiazheng Luo, Xiaoyuan Luo +3
3D point cloud registration is a fundamental problem in computer vision and robotics. Recently, learning-based point cloud registration methods have made great progress. However, t…
Boosting Point-BERT by Multi-choice Tokens
Kexue Fu, Mingzhi Yuan, Manning Wang
Masked language modeling (MLM) has become one of the most successful self-supervised pre-training task. Inspired by its success, Point-BERT, as a pioneer work in point cloud, propo…
DGMIL: Distribution Guided Multiple Instance Learning for Whole Slide Image Classification
Linhao Qu, Xiaoyuan Luo, Shaolei Liu +2
Multiple Instance Learning (MIL) is widely used in analyzing histopathological Whole Slide Images (WSIs). However, existing MIL methods do not explicitly model the data distributio…
POS-BERT: Point Cloud One-Stage BERT Pre-Training
Kexue Fu, Peng Gao, ShaoLei Liu +3
Recently, the pre-training paradigm combining Transformer and masked language modeling has achieved tremendous success in NLP, images, and point clouds, such as BERT. However, dire…
TransFuse: A Unified Transformer-based Image Fusion Framework using Self-supervised Learning
Linhao Qu, Shaolei Liu, Manning Wang +4
Image fusion is a technique to integrate information from multiple source images with complementary information to improve the richness of a single image. Due to insufficient task-…
TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework using Self-Supervised Multi-Task Learning
Linhao Qu, Shaolei Liu, Manning Wang +1
In this paper, we propose TransMEF, a transformer-based multi-exposure image fusion framework that uses self-supervised multi-task learning. The framework is based on an encoder-de…
A Learnable Self-supervised Task for Unsupervised Domain Adaptation on Point Clouds
Xiaoyuan Luo, Shaolei Liu, Kexue Fu +2
Deep neural networks have achieved promising performance in supervised point cloud applications, but manual annotation is extremely expensive and time-consuming in supervised learn…
Robust Point Cloud Registration Framework Based on Deep Graph Matching
Kexue Fu, Shaolei Liu, Xiaoyuan Luo +1
3D point cloud registration is a fundamental problem in computer vision and robotics. There has been extensive research in this area, but existing methods meet great challenges in…
WaveFuse: A Unified Deep Framework for Image Fusion with Discrete Wavelet Transform
Shaolei Liu, Manning Wang, Zhijian Song
We propose an unsupervised image fusion architecture for multiple application scenarios based on the combination of multi-scale discrete wavelet transform through regional energy a…