all AI news
Diff-Reg v1: Diffusion Matching Model for Registration Problem
April 1, 2024, 4:44 a.m. | Qianliang Wu, Haobo Jiang, Lei Luo, Jun Li, Yaqing Ding, Jin Xie, Jian Yang
cs.CV updates on arXiv.org arxiv.org
Abstract: Establishing reliable correspondences is essential for registration tasks such as 3D and 2D3D registration. Existing methods commonly leverage geometric or semantic point features to generate potential correspondences. However, these features may face challenges such as large deformation, scale inconsistency, and ambiguous matching problems (e.g., symmetry). Additionally, many previous methods, which rely on single-pass prediction, may struggle with local minima in complex scenarios. To mitigate these challenges, we introduce a diffusion matching model for robust correspondence …
abstract arxiv challenges cs.cv diff diffusion face features generate however registration scale semantic symmetry tasks type
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer
@ GPTZero | Toronto, Canada
ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)
@ HelloBetter | Remote
Doctoral Researcher (m/f/div) in Automated Processing of Bioimages
@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena
Seeking Developers and Engineers for AI T-Shirt Generator Project
@ Chevon Hicks | Remote
Data Scientist, Mid
@ Booz Allen Hamilton | DEU, Stuttgart (Kurmaecker St)
Tech Excellence Data Scientist
@ Booz Allen Hamilton | Undisclosed Location - USA, VA, Mclean