A new arXiv paper introduces Kaininja, a method that extends native 3D generators beyond producing a single fused mesh. Current systems such as TRELLIS.2 output high-fidelity, non-watertight geometry with materials, but as one combined object, which complicates downstream tasks. The work targets part-level generation to better support editing, rigging and simulation.
Researchers present a transformer-based autoencoder that maps 3D molecules of differing sizes into a single fixed-dimensional latent space, removing the need to fix molecule size in advance. This matters because molecular size is tied to composition, structure and other target properties in drug and materials discovery. The approach is described as equivariant-free, meaning it avoids the geometric constraints commonly used in 3D molecular generators.
A new arXiv paper introduces GLOSS, a method for generating complete textures on 3D objects guided by a single reference view. The authors observe that current conditional image generators struggle to cover a full object surface while staying faithful to the reference look. GLOSS addresses this by exploiting local geometric self-similarity across the shape to propagate texture detail consistently.