OutCast: Outdoor Single-image Relighting with Cast Shadows

• URL: http://arxiv.org/abs/2204.09341v1
• Date: Wed, 20 Apr 2022 09:24:14 GMT
• Title: OutCast: Outdoor Single-image Relighting with Cast Shadows
• Authors: David Griffiths, Tobias Ritschel, Julien Philip
• Abstract summary: We propose a relighting method for outdoor images. Our method mainly focuses on predicting cast shadows in arbitrary novel lighting directions from a single image. Our proposed method achieves, for the first time, state-of-the-art relighting results, with only a single image as input.
• Score: 19.354412901507175
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a relighting method for outdoor images. Our method mainly focuses on predicting cast shadows in arbitrary novel lighting directions from a single image while also accounting for shading and global effects such the sun light color and clouds. Previous solutions for this problem rely on reconstructing occluder geometry, e.g. using multi-view stereo, which requires many images of the scene. Instead, in this work we make use of a noisy off-the-shelf single-image depth map estimation as a source of geometry. Whilst this can be a good guide for some lighting effects, the resulting depth map quality is insufficient for directly ray-tracing the shadows. Addressing this, we propose a learned image space ray-marching layer that converts the approximate depth map into a deep 3D representation that is fused into occlusion queries using a learned traversal. Our proposed method achieves, for the first time, state-of-the-art relighting results, with only a single image as input. For supplementary material visit our project page at: https://dgriffiths.uk/outcast.

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