# IntrinSeqNet: Learning to Estimate the Reflectance from Varying Illumination

## TL;DR

This paper introduces IntrinSeqNet, a novel neural network model designed to estimate surface reflectance from images taken under varying illumination conditions, aiming to improve material appearance understanding.

## Contribution

The work presents a new deep learning framework that effectively estimates reflectance despite changes in lighting, advancing the state of the art in reflectance estimation techniques.

## Key findings

- IntrinSeqNet outperforms existing methods on benchmark datasets.
- The model demonstrates robustness to different illumination variations.
- Significant improvements in reflectance accuracy are achieved.

## Abstract

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