works on

From the 1 of 7 linked papers with an AI index.

activity
20242026
collaborators

7 papers

cs.CV2026

Texture++: Elevating 3D Asset Texture Resolution with a Region-Aware Diffusion Model

Shuaiwei Wang, Shi Li, Jieting Xu +4

Numerous 3D assets are discarded due to low texture resolution, while current super-resolution models ignore texture maps and focus on natural images. An efficient and generalizabl…

cs.CV2026

HIVE-3D: Hierarchical Voxel Enhancement for High-Quality 3D Scene Generation

Bin Zang, Wenting Zheng, Xiaoliang Luo +8

The paper presents HIVE-3D, a method that generates high-quality 3D scenes from a single image by building a hierarchical component tree and applying voxel super‑resolution to prog…

cs.CV2026

GeRM: A Generative Rendering Model From Physically Realistic to Photorealistic

Jiayuan Lu, Rengan Xie, Xuancheng Jin +5

While physically-based rendering (PBR) simulates light transport that guarantees physical realism, achieving true photorealistic rendering (PRR) demands prohibitive time and labor,…

cs.CV2025

LiDAR-GS++:Improving LiDAR Gaussian Reconstruction via Diffusion Priors

Qifeng Chen, Jiarun Liu, Rengan Xie +5

Recent GS-based rendering has made significant progress for LiDAR, surpassing Neural Radiance Fields (NeRF) in both quality and speed. However, these methods exhibit artifacts in e…

cs.GR2025

Fuse3D: Generating 3D Assets Controlled by Multi-Image Fusion

Xuancheng Jin, Rengan Xie, Wenting Zheng +3

Recently, generating 3D assets with the control of condition images has achieved impressive quality. However, existing 3D generation methods are limited to handling a single contro…

cs.GR2024

LDM: Large Tensorial SDF Model for Textured Mesh Generation

Rengan Xie, Wenting Zheng, Kai Huang +5

Previous efforts have managed to generate production-ready 3D assets from text or images. However, these methods primarily employ NeRF or 3D Gaussian representations, which are not…