| --- |
| license: apache-2.0 |
| datasets: |
| - OpenIllumination/OpenIllumination |
| language: |
| - en |
| - ko |
| pipeline_tag: image-to-image |
| --- |
| # 🔦LightTransporter🚀 (2024 Fall CS492D Final Project) |
|
|
| [**Poster**](https://drive.google.com/file/d/101eOfUqfS-wKGuJPvaqoBtKvs4GrIywM/view?usp=sharing) | [**Report**](https://drive.google.com/file/d/1009QskpqLxJRltqiCnim5seDmX1nxwEL/view?usp=sharing) | [**Github**](https://github.com/j-mayo/LightTransporter/) |
| > <b>KAIST 2024 Fall CS492D: Diffusion Models and Their Applications</b> |
|
|
|  |
|
|
| ## Introduction |
| This is a **Team03** official repository of the project in the KAIST 2024 Fall CS492D lecture, [Diffusion Models and Their Applications](https://mhsung.github.io/kaist-cs492d-fall-2024/). |
|
|
| ## Dataset |
| We used [OpenIllumination](https://oppo-us-research.github.io/OpenIllumination/) dataset for our project, and [LiT](https://github.com/KAIST-Visual-AI-Group/Diffusion-Project-Illumination) project repo for downloading and pre-processing. |
|
|
| The image below shows the environment map of each light condition, which we used to encode the light condition. |
|
|
| <img src="https://github.com/user-attachments/assets/7e51df4c-8585-4167-8db6-78e9ecbf1032" width="500" height="200"> |
|
|
| ## Qualitative Results |
| Each row shows the **source**, **target**(ground truth), and **generated images** from left to right. |
|
|
|  |
|
|
|
|
| ## Quantitative Results |
|  |
|
|
| ## Team Information |
| - [Junwoo Choi](https://github.com/Str4Strength) (School of Computing, KAIST) |
| - [Jaeyo Shin](https://github.com/j-mayo) (Graduate School of AI, KAIST) |
| - [Dongwon Choi](https://github.com/chlehdwon) (Graduate School of AI, KAIST) |
|
|
