4 accepted papers
Medical image diagnosis in real clinical scenario faces the challenging open set recognition problem with domain shift. Based on the observation that it is often merely the local lesion areas in the whole image decide or cause the true seen or potential unseen disease labels, we propose a unified de…
Detecting in open-world scenarios poses a formidable challenge for models intended for real-world deployment. The advanced closed set object detectors achieve impressive performance under the closed set setting, but often produce overconfident misprediction on unknown objects due to the lack of supe…
Weakly Supervised Object Localization (WSOL) aims to localize objects with image-level supervision. Existing works mainly rely on Class Activation Mapping (CAM) derived from a classification model. However, CAM-based methods usually focus on the most discriminative parts of an object (i.e., incomple…
Automatic video polyp segmentation (VPS) is highly valued for the early diagnosis of colorectal cancer. However, existing methods are limited in three respects: 1) most of them work on static images, while ignoring the temporal information in consecutive video frames; 2) all of them are fully superv…