NeFII: Inverse Rendering for Reflectance Decomposition with Near-Field Indirect Illumination
- Publisher:
- IEEE
- Publication Type:
- Conference Proceeding
- Citation:
- 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, 2023-June, pp. 4295-4304
- Issue Date:
- 2023-01-01
Closed Access
| Filename | Description | Size | |||
|---|---|---|---|---|---|
| 2303.16617v2.pdf | Submitted version | 3.27 MB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
Inverse rendering methods aim to estimate geometry materials and illumination from multi view RGB images In order to achieve better decomposition recent approaches attempt to model indirect illuminations reflected from different materials via Spherical Gaussians SG which however tends to blur the high frequency reflection details In this paper we propose an end to end inverse rendering pipeline that decomposes materials and illumination from multi view images while considering near field indirect illumination In a nutshell we introduce the Monte Carlo sampling based path tracing and cache the indirect illumination as neural radiance enabling a physics faithful and easy to optimize inverse rendering method To enhance efficiency and practicality we leverage SG to represent the smooth environment illuminations and apply importance sampling techniques To supervise indirect illuminations from unobserved directions we develop a novel radiance consistency constraint between implicit neural radiance and path tracing results of unobserved rays along with the joint optimization of materials and illuminations thus significantly improving the decomposition performance Extensive experiments demonstrate that our method outperforms the state of the art on multiple synthetic and real datasets especially in terms of inter reflection decomposition
Please use this identifier to cite or link to this item: