1 citations · 1 across the 1 of their papers we have counts for
5 papers
Prompt-to-Product: Generative Assembly via Bimanual Manipulation
Ruixuan Liu, Philip Huang, Ava Pun +8
Creating assembly products demands significant manual effort and expert knowledge in 1) designing the assembly and 2) constructing the product. This paper introduces Prompt-to-Prod…
Generating Physically Stable and Buildable Brick Structures from Text
Ava Pun, Kangle Deng, Ruixuan Liu +3
We introduce BrickGPT, the first approach for generating physically stable interconnecting brick assembly models from text prompts. To achieve this, we construct a large-scale, phy…
Efficient Autoregressive Shape Generation via Octree-Based Adaptive Tokenization
Kangle Deng, Hsueh-Ti Derek Liu, Yiheng Zhu +7
Many 3D generative models rely on variational autoencoders (VAEs) to learn compact shape representations. However, existing methods encode all shapes into a fixed-size token, disre…
Cube: A Roblox View of 3D Intelligence
Foundation AI Team, Kiran Bhat, Nishchaie Khanna +44
Foundation models trained on vast amounts of data have demonstrated remarkable reasoning and generation capabilities in the domains of text, images, audio and video. Our goal at Ro…
Tactile DreamFusion: Exploiting Tactile Sensing for 3D Generation
Ruihan Gao, Kangle Deng, Gengshan Yang +2
3D generation methods have shown visually compelling results powered by diffusion image priors. However, they often fail to produce realistic geometric details, resulting in overly…