March 14, 2024, 4:46 a.m. | Linyi Jin, Nilesh Kulkarni, David Fouhey

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.08768v1 Announce Type: new
Abstract: This paper introduces 3DFIRES, a novel system for scene-level 3D reconstruction from posed images. Designed to work with as few as one view, 3DFIRES reconstructs the complete geometry of unseen scenes, including hidden surfaces. With multiple view inputs, our method produces full reconstruction within all camera frustums. A key feature of our approach is the fusion of multi-view information at the feature level, enabling the production of coherent and comprehensive 3D reconstruction. We train our …

3d reconstruction abstract arxiv cs.cv geometry hidden image images inputs multiple novel paper surface type view work

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Senior Principal, Product Strategy Operations, Cloud Data Analytics

@ Google | Sunnyvale, CA, USA; Austin, TX, USA

Data Scientist - HR BU

@ ServiceNow | Hyderabad, India