arXiv Computer Vision

Off the Planckian Locus: Using 2D Chromaticity to Improve In-Camera Color

The paper proposes replacing traditional one-dimensional correlated color temperature (CCT) interpolation with a two-dimensional chromaticity approach for in-camera colorimetric mapping. By training a lightweight multi-layer perceptron (MLP) on a lightbox calibration that includes representative LED sources, the method achieves a 22% average reduction in angular reproduction error across diverse LED lighting. It remains compatible with conventional illuminants, handles multi-illuminant scenes, and can be deployed in real time with minimal computational overhead.

arXiv Computer Vision
Sep 7

E-RGB-D: Real-Time Event-Based Perception with Structured Light

The paper introduces E‑RGB‑D, a real‑time event‑based perception system that combines a Digital Light Processing projector with a monochrome event camera to produce RGB‑D data. By projecting structured light and capturing asynchronous brightness changes, the system can detect color and depth for each pixel, achieving a color detection speed of 1400 fps and a depth detection rate of 4 kHz. The approach enables frameless RGB‑D sensing and delivers colorful point clouds without compromising spatial resolution.

By Seyed Ehsan Marjani Bajestani, Giovanni Beltrame
Hugging Face Trending Papers
Aug 11

Towards Color-Faithful Low-Light Image Enhancement via Adaptive Color Debiasing and Saturation Rectification

Low-light imaging often introduces color bias caused by the low signal-to-noise ratio and the image formation process. Although recent low-light image enhancement methods have achieved strong brightness recovery, faithful color restoration remains challenging, manifesting as overall color bias together with local under- and over-saturation.

arXiv Computer Vision
Sep 11

Shedding Light: A Benchmark for Evaluating Lighting Understanding in Generative Image Models

The paper introduces a benchmark called Shedding Light to evaluate how well generative image models understand and reproduce lighting. The benchmark tests models by asking them to inpaint a simple object, called a light probe, into real photographs and then compares the generated probe to the ground truth to assess lighting direction, colour, and radiance. The authors provide a scalable protocol and open-source code and data for systematic assessment of photometric accuracy in future models.

By Justine Giroux, Jack Oliver Hilliard, Yannick Hold-Geoffroy, Javier Vazquez-Corral, Jean-Fran\c{c}ois Lalonde