2 citations · 3 across the 6 of their papers we have counts for
6 papers
Enhancing Part-Level Point Grounding for Any Open-Source MLLMs
Jin-Cheng Jhang, Fu-En Wang, Xin Yang +4
Visual grounding aims to associate free-form textual queries with specific regions in an image. While recent Multimodal Large Language Models (MLLMs) have demonstrated promising ca…
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…
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…
Enhancing Single Image to 3D Generation using Gaussian Splatting and Hybrid Diffusion Priors
Hritam Basak, Hadi Tabatabaee, Shreekant Gayaka +6
3D object generation from a single image involves estimating the full 3D geometry and texture of unseen views from an unposed RGB image captured in the wild. Accurately reconstruct…
LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matching
Yixun Liang, Xin Yang, Jiantao Lin +3
The recent advancements in text-to-3D generation mark a significant milestone in generative models, unlocking new possibilities for creating imaginative 3D assets across various re…