AI RESEARCH
Every9D-21M: Large-Scale Real-World 9D Canonicalization of Everyday Objects
arXiv CS.CV
•
ArXi:2605.28270v1 Announce Type: new Estimating the 9D pose of everyday objects from a single real-world image remains challenging. This is largely due to the lack of large-scale supervision. Most existing datasets either rely heavily on synthetic renderings or provide limited coverage of real-world objects: the largest real-world 9D pose dataset to date contains only 17K annotated objects across 9 categories.