1 citations · 3 across the 9 of their papers we have counts for
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GaussianProperty: Integrating Physical Properties to 3D Gaussians with LMMs
Xinli Xu, Wenhang Ge, Dicong Qiu +8
Estimating physical properties for visual data is a crucial task in computer vision, graphics, and robotics, underpinning applications such as augmented reality, physical simulatio…
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…
Uni-Renderer: Unifying Rendering and Inverse Rendering Via Dual Stream Diffusion
Zhifei Chen, Tianshuo Xu, Wenhang Ge +7
Rendering and inverse rendering are pivotal tasks in both computer vision and graphics. The rendering equation is the core of the two tasks, as an ideal conditional distribution tr…
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…
X-Ray: A Sequential 3D Representation For Generation
Tao Hu, Wenhang Ge, Yuyang Zhao +1
We introduce X-Ray, a novel 3D sequential representation inspired by the penetrability of x-ray scans. X-Ray transforms a 3D object into a series of surface frames at different lay…
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…