Overview
LTNet, short for Light Transfer Network, is a novel approach aimed at depth-guided image relighting. This project unveils a method to transfer light from a reference image to a target image with the guidance of depth information, achieving impressive image relighting results while preserving the naturalness and photorealism of the scenes. This is a work presented in NTIRE2021 Competition Light Transfer Track, in association with CVPR2021 Workshop.
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Objectives
The primary objectives of the LTNet project include:
- Developing an effective method for image relighting that leverages depth information.
- Demonstrating the advantages of utilizing depth guidance in light transfer networks.
- Enhancing the realism and naturalness of relit images.
Methodology
LTNet employs a dual-stream network architecture:
- The Depth Stream: Processes the depth information of the target image.
- The Light Stream: Extracts light information from the reference image.
These streams interact to produce a light transfer field, which is then utilized to relight the target image. The network is trained with a set of loss functions to ensure the relit image preserves the geometric and photometric properties of the scene.
Results
The results of the LTNet project showcase significant improvements in image relighting, especially in challenging lighting conditions. The method outperforms existing approaches in terms of both quantitative and qualitative evaluations, demonstrating its effectiveness and potential for real-world applications.
Future Work
The success of LTNet paves the way for further exploration and improvements in depth-guided image relighting techniques. Future work may focus on refining the network architecture, expanding the training dataset, and exploring real-time relighting applications.