# Time-Aware Auto White Balance in Mobile Photography

arXiv: https://arxiv.org/abs/2504.05623 · HTML: https://mlsanity.com/paper/2504.05623/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 29 of its 77 references that are in the map.
- First posted on arXiv 8 Apr 2025.

## Builds on (most cited first, 29 of 29)

- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [SGDR: Stochastic Gradient Descent with Warm Restarts](https://mlsanity.com/paper/1608.03983/) (2016)
- [Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)](https://mlsanity.com/paper/1511.07289/) (2015)
- [Invertible Image Signal Processing](https://mlsanity.com/paper/2103.15061/) (2021)
- [DeepISP: Towards Learning an End-to-End Image Processing Pipeline](https://mlsanity.com/paper/1801.06724/) (2018)
- [Practical Deep Raw Image Denoising on Mobile Devices](https://mlsanity.com/paper/2010.06935/) (2020)
- [Invertible Denoising Network: A Light Solution for Real Noise Removal](https://mlsanity.com/paper/2104.10546/) (2021)
- [Mobile Computational Photography: A Tour](https://mlsanity.com/paper/2102.09000/) (2021)
- [Rethinking Noise Synthesis and Modeling in Raw Denoising](https://mlsanity.com/paper/2110.04756/) (2021)
- [Handheld Mobile Photography in Very Low Light](https://mlsanity.com/paper/1910.11336/) (2019)
- [Deep White-Balance Editing](https://mlsanity.com/paper/2004.01354/) (2020)
- [Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision](https://mlsanity.com/paper/2108.08119/) (2021)
- [Fast Fourier Color Constancy](https://mlsanity.com/paper/1611.07596/) (2016)
- [Convolutional Color Constancy](https://mlsanity.com/paper/1507.00410/) (2015)
- [Cross-Camera Convolutional Color Constancy](https://mlsanity.com/paper/2011.11890/) (2020)
- [CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks](https://mlsanity.com/paper/2006.12709/) (2020)
- [On Finding Gray Pixels](https://mlsanity.com/paper/1901.03198/) (2019)
- [ParamISP: Learned Forward and Inverse ISPs using Camera Parameters](https://mlsanity.com/paper/2312.13313/) (2023)
- [Cascading Convolutional Color Constancy](https://mlsanity.com/paper/1912.11180/) (2019)
- [Sensor-Independent Illumination Estimation for DNN Models](https://mlsanity.com/paper/1912.06888/) (2019)
- [Enhancing RAW-to-sRGB with Decoupled Style Structure in Fourier Domain](https://mlsanity.com/paper/2401.02161/) (2024)
- [MicroISP: Processing 32MP Photos on Mobile Devices with Deep Learning](https://mlsanity.com/paper/2211.06770/) (2022)
- [Approaching the Computational Color Constancy as a Classification Problem through Deep Learning](https://mlsanity.com/paper/1608.07951/) (2016)
- [Bag of Color Features For Color Constancy](https://mlsanity.com/paper/1906.04445/) (2019)
- [The Cube++ Illumination Estimation Dataset](https://mlsanity.com/paper/2011.10028/) (2020)
- [INTEL-TAU: A Color Constancy Dataset](https://mlsanity.com/paper/1910.10404/) (2019)
- [Optimizing Illuminant Estimation in Dual-Exposure HDR Imaging](https://mlsanity.com/paper/2403.02449/) (2024)
- [INRetouch: Context Aware Implicit Neural Representation for Photography Retouching](https://mlsanity.com/paper/2412.03848/) (2024)
- [Robust channel-wise illumination estimation](https://mlsanity.com/paper/2111.05681/) (2021)

## Built on by (most cited first, 10 of 10)

- [Leveraging Multispectral Sensors for Color Correction in Mobile Cameras](https://mlsanity.com/paper/2512.08441/) (2025)
- [RAWild: Sensor-Agnostic RAW Object Detection via Physics-Guided Curve and Grid Modeling](https://mlsanity.com/paper/2605.05941/) (2026)
- [Perception-Inspired Color Space Design for Photo White Balance Editing](https://mlsanity.com/paper/2512.09383/) (2025)
- [Off the Planckian Locus: Using 2D Chromaticity to Improve In-Camera Color](https://mlsanity.com/paper/2511.17133/) (2025)
- [Learning Camera-Agnostic White-Balance Preferences](https://mlsanity.com/paper/2507.01342/) (2025)
- [Raw-JPEG Adapter: Efficient Raw Image Compression with JPEG](https://mlsanity.com/paper/2509.19624/) (2025)
- [Edit-aware RAW Reconstruction](https://mlsanity.com/paper/2512.05859/) (2025)
- [RawGen: Learning Camera Raw Image Generation](https://mlsanity.com/paper/2604.00093/) (2026)
- [Color Pass-Through via Camera-Display Coupling](https://mlsanity.com/paper/2607.12746/) (2026)
- [Towards Color-Faithful Low-Light Image Enhancement via Adaptive Color Debiasing and Saturation Rectification](https://mlsanity.com/paper/2608.10512/) (2026)

## Abstract (arXiv)

Cameras rely on auto white balance (AWB) to correct undesirable color casts caused by scene illumination and the camera's spectral sensitivity. This is typically achieved using an illuminant estimator that determines the global color cast solely from the color information in the camera's raw sensor image. Mobile devices provide valuable additional metadata-such as capture timestamp and geolocation-that offers strong contextual clues to help narrow down the possible illumination solutions. This paper proposes a lightweight illuminant estimation method that incorporates such contextual metadata, along with additional capture information and image colors, into a compact model (~5K parameters), achieving promising results, matching or surpassing larger models. To validate our method, we introduce a dataset of 3,224 smartphone images with contextual metadata collected at various times of day and under diverse lighting conditions. The dataset includes ground-truth illuminant colors, determined using a color chart, and user-preferred illuminants validated through a user study, providing a comprehensive benchmark for AWB evaluation.