We introduce MeshAnything V2, an autoregressive transformer that generates Artist-Created
Meshes (AM) aligned to given shapes. It can be integrated with various 3D asset production …

This paper introduces CoFie, a novel local geometry-aware neural surface representation.
CoFie is motivated by the theoretical analysis of local SDFs with quadratic approximation …

The increasing demand for high-quality 3D assets across various industries necessitates
efficient and automated 3D content creation. Despite recent advancements in 3D generative …

We introduce a new approach for generating realistic 3D models with UV maps through a
representation termed" Object Images." This approach encapsulates surface geometry …

Autoregressive transformers have revolutionized generative models in language processing
and shown substantial promise in image and video generation. However, these models face …

Recent texture generation methods achieve impressive results due to the powerful
generative prior they leverage from large-scale text-to-image diffusion models. However …

This work explores expanding the capabilities of large language models (LLMs) pretrained
on text to generate 3D meshes within a unified model. This offers key advantages of (1) …

Autoregressive models have demonstrated remarkable success across various fields, from
large language models (LLMs) to large multimodal models (LMMs) and 2D content …

While 3D content generation has advanced significantly, existing methods still face
challenges with input formats, latent space design, and output representations. This paper …

We present PhyCAGE, the first approach for physically plausible compositional 3D asset
generation from a single image. Given an input image, we first generate consistent multi …