Yanlin Qian

I am a color&luma ISP research engineer, with my enthusiasm on making realtime low-ppa Computational photography algorithms and its product implementation. I work for DJI/HasselBlad now.

I am an ex-Huawei&Honor&MicroBT engineer. I work on a bunch but still quite narrow ISP problems, for example auto-white balance (awb), illumination reflentance spectra estimation, chromatic adaption, blc lsc ccm ae and so on. I graduated from Phd in Tampere University in December 2020, where I was supervised by Prof. Joni-Kristian Kämäräinen and Prof. Jiri Matas.

Email  /  Google Scholar  /  Linkedin

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Research

c4_track.png Learning Triangular Distribution in Visual World
Ping Chen, Xingpeng Zhang, Chengtao Zhou, Dichao Fan, Peng Tu, Le Zhang, Yanlin Qian(corresponding author)
CVPR,2024

Built on trigular distribution, we learn an injective function mapping feature difference to label difference linearly. We prove it useful in 3 tasks: Facial Age Recognition, Illumination Chromaticity Estimation, and Aesthetics assessment.

c4_track.png Point Cloud Color Constancy
Xiaoyan Xing, Yanlin Qian(Equal First),Sibo Feng, Yuhan Dong, Jiri Matas
CVPR,2022

The first awb work tacking awb problem in the world of the 3d point cloud, captured with rgb sensor and a TOF sensor.

c4_track.png Fast Fourier Intrinsic Network
Yanlin Qian, Miaojing Shi, Joni-Kristian Kämäräinen, Jiri Matas
WACV,2020

To address the problem of decomposing an image into albedo and shading, we propose the Fast Fourier Intrinsic Network, FFI-Net in short, that operates in the spectral domain, splitting the input into several spectral bands.

c4_track.png SDE-AWB: a Generic Solution for 2nd International Illumination Estimation Challenge
Yanlin Qian, Sibo Feng, Kang Qian, Miaofeng Wang
ICMV illumination estimation challenge,2020

We propose a neural network-based solution for three different tracks of 2nd International Illumination Estimation Challenge. SDE-AWB obtains 1st place in both indoor and two-illuminant tracks and 2nd place in general track.

A Benchmark for Temporal Color Constancy
Yanlin Qian, Jani Käpylä, Joni-Kristian Kämäräinen, Samu Koskinen, Jiri Matas
ECCV workshop 2020
bibtex/ data/ code

Revisiting Temporal color constancy. We propose a 600-video temporal color constancy dataset, and a smaller better faster net called TCC-Net.

c4_track.png Cascading Convolutional Color Constancy
Huanglin Yu, Ke Chen, Kaiqi Wang, Yanlin Qian, Zhaoxiang Zhang, Kui Jia
AAAI,2020
code/ bibtex

We cascade SqueezeNet-based bricks obtain SotA results on Gehlershi and NUS 8-camera datasets.

graypixel2019.png On Finding Gray Pixels
Yanlin Qian, Joni Kämäräinen, Jarno Nikkanen, Jiri Matas
CVPR, 2019
code/ supplement / bibtex

Gray (achromatic) pixels can be used for illumination estimation. This paper tells how to pick up them ACCURATELY.

graypixel_meanshift.png Revisiting Gray Pixel for Statistical Illumination Estimation
Yanlin Qian, Said Pertuz, Joni Kämäräinen, Jarno Nikkanen, Jiri Matas
VISSAP, 2019
code / bibtex

Gray (achromatic) pixels can be used for illumination estimation. This paper tells how to pick up them using Clustering.

flashgraypixel.png Flash Lightens Gray Pixels
Yanlin Qian, Song Yan, Joni Kämäräinen, Jiri Matas
ICIP, 2019
bibtex

Gray (achromatic) pixels can be used for illumination estimation. This paper tells how to pick up them with the help of flash photography.

challenge.png Fast Fourier Color Constancy and Grayness Index for ISPA Illumination Estimation Challenge
Yanlin Qian,Ke Chen, Huanglin Yu
ISPA, International Workshop on Color Vision, 2019
bibtex / Leaderboard Page

We briefly introduce two submissions to the Illumination Estimation Challenge, in the Int'l Workshop on Color Vision, affiliated to the 11th Int'l Symposium on Image and Signal Processing and Analysis. The fourier-transform-based submission is ranked 3rd, and the statistical Gray-pixel-based one ranked 6th.

Recurrent Color Constancy
Yanlin Qian, Ke Chen, Joni Kämäräinen, Jarno Nikkanen, Jiri Matas
ICCV, 2017
bibtex

Temporal color constancy: measuring the illumination of the captured image based on image deque.

msvr.png Deep Structured-Output Regression Learning for Computational Color Constancy
Yanlin Qian, Ke Chen, Joni-Kristian Kamarainen, Jarno Nikkanen, Jiri Matas
ICPR, 2016
bibtex

Illumination estimation based on VGG and AlexNet feature map and multi-output regression. This is my first paper.

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