Search Results for author: Xiaoxuan Yu

Found 3 papers, 1 papers with code

DOCTR: Disentangled Object-Centric Transformer for Point Scene Understanding

1 code implementation25 Mar 2024 Xiaoxuan Yu, Hao Wang, Weiming Li, Qiang Wang, SoonYong Cho, Younghun Sung

In this work, we propose a novel Disentangled Object-Centric TRansformer (DOCTR) that explores object-centric representation to facilitate learning with multiple objects for the multiple sub-tasks in a unified manner.

Decoder Object +1

Semi-supervised Cell Recognition under Point Supervision

no code implementations14 Jun 2023 Zhongyi Shui, Yizhi Zhao, Sunyi Zheng, Yunlong Zhang, Honglin Li, Shichuan Zhang, Xiaoxuan Yu, Chenglu Zhu, Lin Yang

Overall, we use the current models to generate pseudo labels for unlabeled images, which are in turn utilized to supervise the models training.

whole slide images

DPA-P2PNet: Deformable Proposal-aware P2PNet for Accurate Point-based Cell Detection

no code implementations5 Mar 2023 Zhongyi Shui, Sunyi Zheng, Chenglu Zhu, Shichuan Zhang, Xiaoxuan Yu, Honglin Li, Jingxiong Li, Pingyi Chen, Lin Yang

Unlike mainstream PCD methods that rely on intermediate density map representations, the Point-to-Point network (P2PNet) has recently emerged as an end-to-end solution for PCD, demonstrating impressive cell detection accuracy and efficiency.

Cell Detection

Cannot find the paper you are looking for? You can Submit a new open access paper.