Reproduce “Solv3R: 3D Looped Transformer as a Multi-view Solver” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Jeong-gi Kwak, Andrea Tagliasacchi, Sho Kagami, Yuki Ono, Kwang Moo Yi
Solv3R incrementally refines multi-view 3D reconstructions as new images arrive, using a shared transformer update that can continue from existing view states. In a 64-view evaluation, continuing with 8 calls per insertion achieved pose AUC@10 of 92.2, versus 91.8 for restarting with 16 calls; this supports fewer calls for comparable accuracy, but stationary updates do not guarantee correct geometry.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.