Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.03748 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915916089917440 |
|---|---|
| author | Li, Wei Sun, Hanxiao Huang, Tao Wang, Haoxiang Wang, Tongtong Pan, Zherong Wu, Kui |
| author_facet | Li, Wei Sun, Hanxiao Huang, Tao Wang, Haoxiang Wang, Tongtong Pan, Zherong Wu, Kui |
| contents | Participating media are a pervasive and intriguing visual effect in virtual environments. Unfortunately, rendering such phenomena in real-time is notoriously difficult due to the computational expense of estimating the volume rendering equation. While the six-way lightmaps technique has been widely used in video games to render smoke with a camera-oriented billboard and approximate lighting effects using six precomputed lightmaps, achieving a balance between realism and efficiency, it is limited to pre-simulated animation sequences and is ignorant of camera movement. In this work, we propose a neural six-way lightmaps method to strike a long-sought balance between dynamics and visual realism. Our approach first generates a guiding map from the camera view using ray marching with a large sampling distance to approximate smoke scattering and silhouette. Then, given a guiding map, we train a neural network to predict the corresponding six-way lightmaps. The resulting lightmaps can be seamlessly used in existing game engine pipelines. This approach supports visually appealing rendering effects while enabling real-time user interactivity, including smoke-obstacle interaction, camera movement, and light change. By conducting a series of comprehensive benchmarks, we demonstrate that our method is well-suited for real-time applications, such as games and VR/AR. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_03748 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Real-time Neural Six-way Lightmaps Li, Wei Sun, Hanxiao Huang, Tao Wang, Haoxiang Wang, Tongtong Pan, Zherong Wu, Kui Graphics Computer Vision and Pattern Recognition Participating media are a pervasive and intriguing visual effect in virtual environments. Unfortunately, rendering such phenomena in real-time is notoriously difficult due to the computational expense of estimating the volume rendering equation. While the six-way lightmaps technique has been widely used in video games to render smoke with a camera-oriented billboard and approximate lighting effects using six precomputed lightmaps, achieving a balance between realism and efficiency, it is limited to pre-simulated animation sequences and is ignorant of camera movement. In this work, we propose a neural six-way lightmaps method to strike a long-sought balance between dynamics and visual realism. Our approach first generates a guiding map from the camera view using ray marching with a large sampling distance to approximate smoke scattering and silhouette. Then, given a guiding map, we train a neural network to predict the corresponding six-way lightmaps. The resulting lightmaps can be seamlessly used in existing game engine pipelines. This approach supports visually appealing rendering effects while enabling real-time user interactivity, including smoke-obstacle interaction, camera movement, and light change. By conducting a series of comprehensive benchmarks, we demonstrate that our method is well-suited for real-time applications, such as games and VR/AR. |
| title | Real-time Neural Six-way Lightmaps |
| topic | Graphics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2604.03748 |