# Point Cloud Color Constancy

arXiv: https://arxiv.org/abs/2111.11280 · HTML: https://mlsanity.com/paper/2111.11280/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 52 references that are in the map.
- First posted on arXiv 22 Nov 2021.

## Builds on (most cited first, 14 of 14)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation](https://mlsanity.com/paper/1612.00593/) (2016)
- [PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space](https://mlsanity.com/paper/1706.02413/) (2017)
- [PointCNN: Convolution On X-Transformed Points](https://mlsanity.com/paper/1801.07791/) (2018)
- [Volumetric and Multi-View CNNs for Object Classification on 3D Data](https://mlsanity.com/paper/1604.03265/) (2016)
- [DIODE: A Dense Indoor and Outdoor DEpth Dataset](https://mlsanity.com/paper/1908.00463/) (2019)
- [DepthTrack : Unveiling the Power of RGBD Tracking](https://mlsanity.com/paper/2108.13962/) (2021)
- [Fast Fourier Color Constancy](https://mlsanity.com/paper/1611.07596/) (2016)
- [Convolutional Color Constancy](https://mlsanity.com/paper/1507.00410/) (2015)
- [CLCC: Contrastive Learning for Color Constancy](https://mlsanity.com/paper/2106.04989/) (2021)
- [On Finding Gray Pixels](https://mlsanity.com/paper/1901.03198/) (2019)
- [Cascading Convolutional Color Constancy](https://mlsanity.com/paper/1912.11180/) (2019)
- [Color Constancy Using CNNs](https://mlsanity.com/paper/1504.04548/) (2015)
- [Color Constancy by Learning to Predict Chromaticity from Luminance](https://mlsanity.com/paper/1506.02167/) (2015)

## Built on by (most cited first, 4 of 4)

- [Optimizing Illuminant Estimation in Dual-Exposure HDR Imaging](https://mlsanity.com/paper/2403.02449/) (2024)
- [Perception-Inspired Color Space Design for Photo White Balance Editing](https://mlsanity.com/paper/2512.09383/) (2025)
- [Intrinsic Image Decomposition Using Point Cloud Representation](https://mlsanity.com/paper/2307.10924/) (2023)
- [Relighting as a Probe of Visual Priors via Augmented Latent Intrinsics](https://mlsanity.com/paper/2602.01391/) (2026)

## Abstract (arXiv)

In this paper, we present Point Cloud Color Constancy, in short PCCC, an illumination chromaticity estimation algorithm exploiting a point cloud. We leverage the depth information captured by the time-of-flight (ToF) sensor mounted rigidly with the RGB sensor, and form a 6D cloud where each point contains the coordinates and RGB intensities, noted as (x,y,z,r,g,b). PCCC applies the PointNet architecture to the color constancy problem, deriving the illumination vector point-wise and then making a global decision about the global illumination chromaticity. On two popular RGB-D datasets, which we extend with illumination information, as well as on a novel benchmark, PCCC obtains lower error than the state-of-the-art algorithms. Our method is simple and fast, requiring merely 16*16-size input and reaching speed over 500 fps, including the cost of building the point cloud and net inference.