Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects · HackerPapers discussionshttps://hackerpaper.kaipfister.de/p/1809.10790/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMTDeep Object Pose Estimation for Semantic Robotic Grasping of Household Objects — mentioned by mudshttps://news.ycombinator.com/item?id=28795355urn:hackerpapers:mention:1809.10790:28795355Fri, 08 Oct 2021 03:16:44 GMT<p>Yup! There are a ton of examples of this in robot learning. For instance: https://arxiv.org/abs/1809.10790 by NVIDIA uses photorealistic images and something we call domain randomization to efficiently bridge the sim2real gap for robot grasping. A core issue seems to be that the better the simulation, the harder it is to generate (compute wise) but simple tweaks to the generative process also go a long way.</p><p><a href="https://hackerpaper.kaipfister.de/p/1809.10790/">Paper and discussion history</a>. A mention is not an endorsement.</p>cs.RO