Kechun Liu

Kechun Liu

Ph.D candidate in Computer Science & Engineering, University of Washington, advised by Prof. Linda Shapiro

Publications

  1. Liu, Kechun, Yitong Jiang, Inchang Choi, Jinwei Gu. “Learning Image-Adaptive Codebooks for Class-Agnostic Image Restoration.” ICCV 2023(To appear). ArXiv; Website; Code

  2. Liu, Kechun, et al. “VSGD-Net: Virtual Staining Guided Melanocyte Detection on Histopathological Images.” Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision. 2023. PDF; Code

  3. Nofallah, Shima, Linda G. Shapiro, Wenjun Wu, Kechun Liu, Fatemeh Ghezloo, and Joann Elmore. “Automated Analysis of Whole Slide Digital Skin Biopsy Images.” Frontiers in Artificial Intelligence: 209.

  4. Liu, Kechun, Mojgan Mokhtari, Beibin Li, Shima Nofallah, Caitlin May, Oliver Chang, Stevan Knezevich, Joann Elmore, and Linda Shapiro. “Learning Melanocytic Proliferation Segmentation in Histopathology Images From Imperfect Annotations.” In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2021. PDF

  5. Zong, Zefang, Jie Feng, Kechun Liu, Hongzhi Shi, and Yong Li. “DeepDPM: Dynamic population mapping via deep neural network.” In Proceedings of the AAAI Conference on Artificial Intelligence, 2019. PDF