6 papers · 1 filter
Advancing high-fidelity 3D and Texture Generation with 2.5D latents
Xin Yang, Jiantao Lin, Yingjie Xu +2
Despite the availability of large-scale 3D datasets and advancements in 3D generative models, the complexity and uneven quality of 3D geometry and texture data continue to hinder t…
DiMeR: Disentangled Mesh Reconstruction Model
Lutao Jiang, Jiantao Lin, Kanghao Chen +7
We propose DiMeR, a novel geometry-texture disentangled feed-forward model with 3D supervision for sparse-view mesh reconstruction. Existing methods confront two persistent obstacl…
PRM: Photometric Stereo based Large Reconstruction Model
Wenhang Ge, Jiantao Lin, Guibao Shen +4
We propose PRM, a novel photometric stereo based large reconstruction model to reconstruct high-quality meshes with fine-grained local details. Unlike previous large reconstruction…
FlexGen: Flexible Multi-View Generation from Text and Image Inputs
Xinli Xu, Wenhang Ge, Jiantao Lin +5
In this work, we introduce FlexGen, a flexible framework designed to generate controllable and consistent multi-view images, conditioned on a single-view image, or a text prompt, o…
LLM-Optic: Unveiling the Capabilities of Large Language Models for Universal Visual Grounding
Haoyu Zhao, Wenhang Ge, Ying-cong Chen
Visual grounding is an essential tool that links user-provided text queries with query-specific regions within an image. Despite advancements in visual grounding models, their abil…
SG-Adapter: Enhancing Text-to-Image Generation with Scene Graph Guidance
Guibao Shen, Luozhou Wang, Jiantao Lin +9
Recent advancements in text-to-image generation have been propelled by the development of diffusion models and multi-modality learning. However, since text is typically represented…