4 citations · 4 across the 2 of their papers we have counts for
6 papers · 1 filter
TexSpot: 3D Texture Enhancement with Spatially-uniform Point Latent Representation
Ziteng Lu, Yushuang Wu, Chongjie Ye +7
High-quality 3D texture generation remains a fundamental challenge due to the view-inconsistency inherent in current mainstream multi-view diffusion pipelines. Existing representat…
Low-Light Video Enhancement with An Effective Spatial-Temporal Decomposition Paradigm
Xiaogang Xu, Kun Zhou, Tao Hu +4
Low-Light Video Enhancement (LLVE) seeks to restore dynamic or static scenes plagued by severe invisibility and noise. In this paper, we present an innovative video decomposition s…
Enhancing Diffusion-based Restoration Models via Difficulty-Adaptive Reinforcement Learning with IQA Reward
Xiaogang Xu, Ruihang Chu, Jian Wang +6
Reinforcement Learning (RL) has recently been incorporated into diffusion models, e.g., tasks such as text-to-image. However, directly applying existing RL methods to diffusion-bas…
MaterialPicker: Multi-Modal DiT-Based Material Generation
Xiaohe Ma, Valentin Deschaintre, Miloš Hašan +4
High-quality material generation is key for virtual environment authoring and inverse rendering. We propose MaterialPicker, a multi-modal material generator leveraging a Diffusion…
ARM: Appearance Reconstruction Model for Relightable 3D Generation
Xiang Feng, Chang Yu, Zoubin Bi +6
Recent image-to-3D reconstruction models have greatly advanced geometry generation, but they still struggle to faithfully generate realistic appearance. To address this, we introdu…
GS^3: Efficient Relighting with Triple Gaussian Splatting
Zoubin Bi, Yixin Zeng, Chong Zeng +4
We present a spatial and angular Gaussian based representation and a triple splatting process, for real-time, high-quality novel lighting-and-view synthesis from multi-view point-l…