all AI news
Power Variable Projection for Initialization-Free Large-Scale Bundle Adjustment
May 9, 2024, 4:45 a.m. | Simon Weber, Je Hyeong Hong, Daniel Cremers
cs.CV updates on arXiv.org arxiv.org
Abstract: Initialization-free bundle adjustment (BA) remains largely uncharted. While Levenberg-Marquardt algorithm is the golden method to solve the BA problem, it generally relies on a good initialization. In contrast, the under-explored Variable Projection algorithm (VarPro) exhibits a wide convergence basin even without initialization. Coupled with object space error formulation, recent works have shown its ability to solve (small-scale) initialization-free bundle adjustment problem. We introduce Power Variable Projection (PoVar), extending a recent inverse expansion method based on …
abstract algorithm arxiv contrast convergence cs.cv error free good object power projection scale solve space type while
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Software Engineer for AI Training Data (School Specific)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Python)
@ G2i Inc | Remote
Software Engineer for AI Training Data (Tier 2)
@ G2i Inc | Remote
Data Engineer
@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania
Artificial Intelligence – Bioinformatic Expert
@ University of Texas Medical Branch | Galveston, TX
Lead Developer (AI)
@ Cere Network | San Francisco, US