Wang, Liansheng

17 publications

ICLR 2026 OpenFly: A COMPREHENSIVE PLATFORM for AERIAL VISION-LANGUAGE NAVIGATION Yunpeng Gao, Chenhui Li, Zhongrui You, Junli Liu, Li Zhen, Pengan Chen, Qizhi Chen, Zhonghan Tang, Liansheng Wang, Yangpenghui, Yiwen Tang, Yuhang Tang, Shuai Liang, Songyi Zhu, Ziqin Xiong, Yifei Su, Xinyi Ye, Jianan Li, Yan Ding, Dong Wang, Zhigang Wang, Bin Zhao, Xuelong Li

ICCV 2025 C2MIL: Synchronizing Semantic and Topological Causalities in Multiple Instance Learning for Robust and Interpretable Survival Analysis Min Cen, Zhenfeng Zhuang, Yuzhe Zhang, Min Zeng, Baptiste Magnier, Lequan Yu, Hong Zhang, Liansheng Wang

NeurIPS 2025 D-VST: Diffusion Transformer for Pathology-Correct Tone-Controllable Cross-Dye Virtual Staining of Whole Slide Images Shurong Yang, Dong Wei, Yihuang Hu, Qiong Peng, Hong Liu, Yawen Huang, Xian Wu, Yefeng Zheng, Liansheng Wang

AAAI 2025 Dynamic Entity-Masked Graph Diffusion Model for Histopathology Image Representation Learning Zhenfeng Zhuang, Min Cen, Yanfeng Li, Fangyu Zhou, Lequan Yu, Baptiste Magnier, Liansheng Wang

AAAI 2024 Boosting Multiple Instance Learning Models for Whole Slide Image Classification: A Model-Agnostic Framework Based on Counterfactual Inference Weiping Lin, Zhenfeng Zhuang, Lequan Yu, Liansheng Wang

AAAI 2024 Federated Modality-Specific Encoders and Multimodal Anchors for Personalized Brain Tumor Segmentation Qian Dai, Dong Wei, Hong Liu, Jinghan Sun, Liansheng Wang, Yefeng Zheng

CVPR 2024 Generalizable Whole Slide Image Classification with Fine-Grained Visual-Semantic Interaction Hao Li, Ying Chen, Yifei Chen, Rongshan Yu, Wenxian Yang, Liansheng Wang, Bowen Ding, Yuchen Han

ICLR 2023 Advancing Radiograph Representation Learning with Masked Record Modeling Hong-Yu Zhou, Chenyu Lian, Liansheng Wang, Yizhou Yu

AAAI 2023 M3AE: Multimodal Representation Learning for Brain Tumor Segmentation with Missing Modalities Hong Liu, Dong Wei, Donghuan Lu, Jinghan Sun, Liansheng Wang, Yefeng Zheng

CVPR 2023 Why Is the Winner the Best? Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu D. Tizabi, Fabian Isensee, Tim J. Adler, Sharib Ali, Vincent Andrearczyk, Marc Aubreville, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Veronika Cheplygina, Marie Daum, Marleen de Bruijne, Adrien Depeursinge, Reuben Dorent, Jan Egger, David G. Ellis, Sandy Engelhardt, Melanie Ganz, Noha Ghatwary, Gabriel Girard, Patrick Godau, Anubha Gupta, Lasse Hansen, Kanako Harada, Mattias P. Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Pierre Jannin, Ali Emre Kavur, Oldřich Kodym, Michal Kozubek, Jianning Li, Hongwei Li, Jun Ma, Carlos Martín-Isla, Bjoern Menze, Alison Noble, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Tim Rädsch, Jonathan Rafael-Patiño, Vivek Singh Bawa, Stefanie Speidel, Carole H. Sudre, Kimberlin van Wijnen, Martin Wagner, Donglai Wei, Amine Yamlahi, Moi Hoon Yap, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Dogu Baran Aydogan, Binod Bhattarai, Louise Bloch, Raphael Brüngel, Jihoon Cho, Chanyeol Choi, Qi Dou, Ivan Ezhov, Christoph M. Friedrich, Clifton D. Fuller, Rebati Raman Gaire, Adrian Galdran, Álvaro García Faura, Maria Grammatikopoulou, SeulGi Hong, Mostafa Jahanifar, Ikbeom Jang, Abdolrahim Kadkhodamohammadi, Inha Kang, Florian Kofler, Satoshi Kondo, Hugo Kuijf, Mingxing Li, Minh Luu, Tomaž Martinčič, Pedro Morais, Mohamed A. Naser, Bruno Oliveira, David Owen, Subeen Pang, Jinah Park, Sung-Hong Park, Szymon Plotka, Elodie Puybareau, Nasir Rajpoot, Kanghyun Ryu, Numan Saeed, Adam Shephard, Pengcheng Shi, Dejan Štepec, Ronast Subedi, Guillaume Tochon, Helena R. Torres, Helene Urien, João L. Vilaça, Kareem A. Wahid, Haojie Wang, Jiacheng Wang, Liansheng Wang, Xiyue Wang, Benedikt Wiestler, Marek Wodzinski, Fangfang Xia, Juanying Xie, Zhiwei Xiong, Sen Yang, Yanwu Yang, Zixuan Zhao, Klaus Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

AAAI 2022 Boost Supervised Pretraining for Visual Transfer Learning: Implications of Self-Supervised Contrastive Representation Learning Jinghan Sun, Dong Wei, Kai Ma, Liansheng Wang, Yefeng Zheng

AAAI 2022 H2-MIL: Exploring Hierarchical Representation with Heterogeneous Multiple Instance Learning for Whole Slide Image Analysis Wentai Hou, Lequan Yu, Chengxuan Lin, Helong Huang, Rongshan Yu, Jing Qin, Liansheng Wang

ECCV 2022 Personalizing Federated Medical Image Segmentation via Local Calibration Jiacheng Wang, Yueming Jin, Liansheng Wang

AAAI 2022 Separated Contrastive Learning for Organ-at-Risk and Gross-Tumor-Volume Segmentation with Limited Annotation Jiacheng Wang, Xiaomeng Li, Yiming Han, Jing Qin, Liansheng Wang, Qichao Zhou

AAAI 2021 Alternative Baselines for Low-Shot 3D Medical Image Segmentation - An Atlas Perspective Shuxin Wang, Shilei Cao, Dong Wei, Cong Xie, Kai Ma, Liansheng Wang, Deyu Meng, Yefeng Zheng

CVPR 2020 LT-Net: Label Transfer by Learning Reversible Voxel-Wise Correspondence for One-Shot Medical Image Segmentation Shuxin Wang, Shilei Cao, Dong Wei, Renzhen Wang, Kai Ma, Liansheng Wang, Deyu Meng, Yefeng Zheng

WACV 2018 ScanNet: A Fast and Dense Scanning Framework for Metastastic Breast Cancer Detection from Whole-Slide Image Huangjing Lin, Hao Chen, Qi Dou, Liansheng Wang, Jing Qin, Pheng-Ann Heng