Learning Intrinsic Image Decomposition from Watching the World

04/02/2018
by   Zhengqi Li, et al.
0

Single-view intrinsic image decomposition is a highly ill-posed problem, and so a promising approach is to learn from large amounts of data. However, it is difficult to collect ground truth training data at scale for intrinsic images. In this paper, we explore a different approach to learning intrinsic images: observing image sequences over time depicting the same scene under changing illumination, and learning single-view decompositions that are consistent with these changes. This approach allows us to learn without ground truth decompositions, and to instead exploit information available from multiple images when training. Our trained model can then be applied at test time to single views. We describe a new learning framework based on this idea, including new loss functions that can be efficiently evaluated over entire sequences. While prior learning-based methods achieve good performance on specific benchmarks, we show that our approach generalizes well to several diverse datasets, including MIT intrinsic images, Intrinsic Images in the Wild and Shading Annotations in the Wild.

READ FULL TEXT

page 1

page 3

page 5

page 7

page 8

research
08/26/2018

CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering

Intrinsic image decomposition is a challenging, long-standing computer v...
research
11/20/2020

Intrinsic Image Decomposition using Paradigms

Intrinsic image decomposition is the classical task of mapping image to ...
research
05/02/2017

Shading Annotations in the Wild

Understanding shading effects in images is critical for a variety of vis...
research
01/11/2017

Revisiting Deep Intrinsic Image Decompositions

While invaluable for many computer vision applications, decomposing a na...
research
12/15/2016

Reflectance Adaptive Filtering Improves Intrinsic Image Estimation

Separating an image into reflectance and shading layers poses a challeng...
research
03/02/2018

Deep Unsupervised Intrinsic Image Decomposition by Siamese Training

We harness modern intrinsic decomposition tools based on deep learning t...
research
04/08/2022

Invariant Descriptors for Intrinsic Reflectance Optimization

Intrinsic image decomposition aims to factorize an image into albedo (re...

Please sign up or login with your details

Forgot password? Click here to reset