5 papers · 2 filters
Image Segmentation in Foundation Model Era: A Survey
Tianfei Zhou, Wang Xia, Fei Zhang +5
Image segmentation is a long-standing challenge in computer vision, studied continuously over several decades, as evidenced by seminal algorithms such as N-Cut, FCN, and MaskFormer…
Generalizable Single-Source Cross-modality Medical Image Segmentation via Invariant Causal Mechanisms
Boqi Chen, Yuanzhi Zhu, Yunke Ao +5
Single-source domain generalization (SDG) aims to learn a model from a single source domain that can generalize well on unseen target domains. This is an important task in computer…
Do Vision Foundation Models Enhance Domain Generalization in Medical Image Segmentation?
Kerem Cekmeceli, Meva Himmetoglu, Guney I. Tombak +3
Neural networks achieve state-of-the-art performance in many supervised learning tasks when the training data distribution matches the test data distribution. However, their perfor…
Implicit-Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenes
Qi Ma, Danda Pani Paudel, Ender Konukoglu +1
Neural implicit functions have demonstrated significant importance in various areas such as computer vision, graphics. Their advantages include the ability to represent complex sha…
Vision-Based Neurosurgical Guidance: Unsupervised Localization and Camera-Pose Prediction
Gary Sarwin, Alessandro Carretta, Victor Staartjes +5
Localizing oneself during endoscopic procedures can be problematic due to the lack of distinguishable textures and landmarks, as well as difficulties due to the endoscopic device s…