activity
20242026
most citedLLM-Optic: Unveiling the Capabilities of Large Language Models for Universal Visual Grounding

1 citations · 2 across the 5 of their papers we have counts for

collaborators

9 papers

cs.CV2026

Seg3DParts: Segmentation-Grounded Controllable Part-Level 3D Generation

Jiantao Lin, Meixi Chen, Yingjie Xu +5

Part-level 3D assets are essential for editing, reassembly, and interaction, yet recovering such structure from a single image remains challenging due to occlusion, ambiguous bound…

cs.CV2025

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…

cs.CV2025

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…

cs.GR2025

Kiss3DGen: Repurposing Image Diffusion Models for 3D Asset Generation

Jiantao Lin, Xin Yang, Meixi Chen +7

Diffusion models have achieved great success in generating 2D images. However, the quality and generalizability of 3D content generation remain limited. State-of-the-art methods of…

cs.RO2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 1 cited

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…