| CARVIEW |
UniLight Workshop
ICCV 2025 Workshop
20 Oct. 2025 PM
Room : 318 A
Honolulu, Hawai'i
Overview
Recent advancements in image editing applications such as relighting, compositing, harmonization, and virtual object insertion have opened up new horizons in visual media, augmented reality, and virtual production---especially with the rise of powerful image generative models. However, evaluating the quality of results for these applications is still a significant challenge. Traditional image quality metrics are not always effective in capturing the perceptual realism and subtle effects these technologies aim to achieve. Additionally, relying on user studies can be time-consuming and introduces variability, making comparing methods consistently challenging. To address these issues, this workshop explores and develops standardized evaluation metrics to bridge the gap between quantitative assessment and qualitative perception.
The UniLight workshop brings a platform to discuss and explore these topics:
- Limitations of existing quantitative image quality metrics: Understanding where and why current image quality assessment (IQA) metrics fail to capture the effectiveness of rendering and relighting methods.
- Role of user studies: Evaluating the necessity and design of user studies for rendering and relighting technologies, and how to standardize and complement them.
- Synthetic vs. real data: Debating the merits and challenges of using synthetic data for evaluation, including the creation of photorealistic datasets, and discussing methodologies for effectively using real-world data.
- Emerging Evaluation Metrics: Exploring new metrics and methods for evaluation, including machine learning-based approaches, perceptual studies, and cross-disciplinary metrics.
- Standardization Efforts: Proposing pathways towards the standardization of evaluation metrics and frameworks within the community.
Invited Speakers
Belen Masia is a tenured Associate Professor in the Computer Science Department at Universidad de Zaragoza, Spain, and a member of the Graphics & Imaging Lab. Her research focuses on the areas of material appearance modeling and virtual reality, with a focus on leveraging human perception to improve content creation tools and algorithms.
Manmohan Chandraker is a full professor in the CSE department of the University of California, San Diego. His interests are in computer vision and machine learning, with applications in self-driving and augmented reality.
Julien Philip is a Senior Research Scientist at Netflix Eyeline Studios working on computer graphics, vision, and machine learning. He is interested in neural rendering, multiview image editing, and relighting.
David Lindell is an Assistant Professor at University of Toronto and Vector Institute working on physically based intelligent sensing. He recently worked on inverse rendering and relighting, as well as novel ways to model light.
Ko Nishino is a professor at Kyoto University's Graduate School of Informatics, where he leads the Computer Vision Laboratory. His research is focused on establishing the theoretical foundations and efficient implementations of computational methods for better understanding people, objects and scenes from their appearance in images and video, as well as the development of novel computational imaging systems that can see beyond what we see.
Schedule
Format and logistics: The workshop is held in person.
Our program features invited speakers, panel discussion, as well as invited and accepted papers.
| Time | Event |
|---|---|
| 1:00 PM – 1:10 PM | Welcome and Introductions |
| 1:10 PM – 2:10 PM | Invited Talks (30 mins x 2) |
| 2:10 PM – 3:10 PM | Contributed Talks (10 mins x 6) |
| 3:10 PM – 3:45 PM | Break and Posters |
| 3:45 PM – 5:15 PM | Invited Talks (30 mins x 3) |
Organizers
David Serrano-Lozano
Social Media Chair
U. Autònoma de Barcelona
Call for Papers
We welcome submissions related to lighting and its perception across various contexts. Both novel research and previously published work are acceptable. Submissions may take the form of posters, extended abstracts or full papers. Concurrent work is also encouraged to foster discussion across disciplines. All submissions will be reviewed for relevance by our organizing committee. Please note that this workshop will not produce formal proceedings.
Submissions are handled through OpenReview at this link. We accept the following submission in two tracks:
- Published Work: This track is for peer-reviewed work that has already been published. In your submission, please provide the reference to the original work on a separate page, including the publication venue.
- Novel Work: This track welcomes early-stage research that has not yet undergone peer review. We actively encourage the submission of works-in-progress and emerging ideas to promote discussion and collaboration among participants.
The submissions of both tracks will be reviewed for relevancy and soundness.
Published work can be of any format. Novel work can be of either of these formats:
- Paper: Maximum 8 pages (excluding references).
- Extended Abstract: Maximum 2 pages.
- Poster: Please use the ICCV'25 poster format.
All submissions should be in PDF format and follow the ICCV 2025 formatting guidelines. The accepted submissions will be presented by the authors at the workshop.
Timeline
| Submission Deadline | |
| Notification of Acceptance | |
| Workshop Date | October 20th, 2025 PM |
Accepted Papers
Temperature-calibrated Style-aware Fusion for Perceptual Quality Assessment of AI-Generated Images
Shivaanee Eswaran, Tushar Shinde
WildLight: A Real-World Dataset and Benchmark for Single-Image Relighting
Lezhong Wang, Mehmet Onurcan Kaya, Siavash Bigdeli, Jeppe Revall Frisvad
Materialist: Physically Based Editing Using Single-Image Inverse Rendering
Lezhong Wang, Duc Minh Tran
Objectness Similarity: Capturing Object-Level Fidelity in 3D Scene Evaluation
Yuiko Uchida, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama
GenLit: Reformulating Single-Image Relighting as Video Generation
Shrisha Bharadwaj, Haiwen Feng, Giorgio Becherini, Victoria Fernandez Abrevaya, Michael J. Black
Exploring LMM-as-a-Judge for Image Harmonization Evaluation
Jeonghun Baek, Eunchung Noh
Acknowledgements
We would like to thank the following organizations for their support:





