DiLightNet: Fine-grained Lighting Control for Diffusion-based Image Generation-Reference-Cited by-同舟云学术

DiLightNet: Fine-grained Lighting Control for Diffusion-based Image Generation

Published:2024-07-13 Issue: Volume:35 Page:1-12
ISSN:
Container-title:Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers '24
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Author:

Zeng Chong¹^ORCID,Dong Yue²^ORCID,Peers Pieter³^ORCID,Kong Youkang⁴^ORCID,Wu Hongzhi⁵^ORCID,Tong Xin²^ORCID

Affiliation:

1. State Key Lab of CAD and CG, Zhejiang University, China and Microsoft Research Asia, China

2. Microsoft Research Asia, China

3. College of William & Mary, United States of America

4. Tsinghua University, China and Microsoft Research Asia, China

5. State Key Lab of CAD and CG, Zhejiang University, China

Funder

Fundamental Research Funds for the Central Universities

Information Technology Center, Zhejiang University

National Science Foundation

National Natural Science Foundation of China

Publisher

ACM

Reference78 articles.

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2. Dina Bashkirova, Arijit Ray, Rupayan Mallick, Sarah Adel Bargal, Jianming Zhang, Ranjay Krishna, and Kate Saenko. 2023. Lasagna: Layered Score Distillation for Disentangled Object Relighting.

3. Shariq Farooq Bhat, Reiner Birkl, Diana Wofk, Peter Wonka, and Matthias Müller. 2023. Zoedepth: Zero-shot transfer by combining relative and metric depth. arXiv preprint arXiv:2302.12288 (2023).

4. Blender Foundation. 2011. Blender Cycles. https://github.com/blender/cycles.

5. Tim Brooks Aleksander Holynski and Alexei A Efros. 2023. Instructpix2pix: Learning to follow image editing instructions. In CVPR. 18392–18402.

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