1 code implementation • 23 Oct 2023 • Yu-Cheng Chou, Bowen Li, Deng-Ping Fan, Alan Yuille, Zongwei Zhou
In summary, this research proposes an efficient annotation strategy for tumor detection and localization that is less accurate than per-pixel annotations but useful for creating large-scale datasets for screening tumors in various medical modalities.
1 code implementation • 6 Aug 2023 • Bowen Li, Yu-Cheng Chou, Shuwen Sun, Hualin Qiao, Alan Yuille, Zongwei Zhou
We further investigate the per-voxel segmentation performance of pancreatic tumors if AI is trained on a combination of CT scans with synthetic tumors and CT scans with annotated large tumors at an advanced stage.
1 code implementation • 25 May 2022 • Ge-Peng Ji, Deng-Ping Fan, Yu-Cheng Chou, Dengxin Dai, Alexander Liniger, Luc van Gool
This paper introduces DGNet, a novel deep framework that exploits object gradient supervision for camouflaged object detection (COD).
4 code implementations • 27 Mar 2022 • Ge-Peng Ji, Guobao Xiao, Yu-Cheng Chou, Deng-Ping Fan, Kai Zhao, Geng Chen, Luc van Gool
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era.
Ranked #2 on Video Polyp Segmentation on SUN-SEG-Easy (Unseen)
no code implementations • 21 May 2021 • Yingxia Jiao, Xiao Wang, Yu-Cheng Chou, Shouyuan Yang, Ge-Peng Ji, Rong Zhu, Ge Gao
Owing to the difficulties of mining spatial-temporal cues, the existing approaches for video salient object detection (VSOD) are limited in understanding complex and noisy scenarios, and often fail in inferring prominent objects.
3 code implementations • 18 May 2021 • Ge-Peng Ji, Yu-Cheng Chou, Deng-Ping Fan, Geng Chen, Huazhu Fu, Debesh Jha, Ling Shao
Existing video polyp segmentation (VPS) models typically employ convolutional neural networks (CNNs) to extract features.
Ranked #6 on Video Polyp Segmentation on SUN-SEG-Easy (Unseen)