no code implementations • 30 Nov 2023 • Ping Chen, Xingpeng Zhang, Chengtao Zhou, Dichao Fan, Peng Tu, Le Zhang, Yanlin Qian
Convolution neural network is successful in pervasive vision tasks, including label distribution learning, which usually takes the form of learning an injection from the non-linear visual features to the well-defined labels.
no code implementations • CVPR 2022 • Xiaoyan Xing, Yanlin Qian, Sibo Feng, Yuhan Dong, Jiri Matas
In this paper, we present Point Cloud Color Constancy, in short PCCC, an illumination chromaticity estimation algorithm exploiting a point cloud.
no code implementations • 31 Dec 2020 • Egor Ershov, Alex Savchik, Ilya Semenkov, Nikola Banić, Karlo Koscević, Marko Subašić, Alexander Belokopytov, Zhihao LI, Arseniy Terekhin, Daria Senshina, Artem Nikonorov, Yanlin Qian, Marco Buzzelli, Riccardo Riva, Simone Bianco, Raimondo Schettini, Sven Lončarić, Dmitry Nikolaev
The main advantage of testing a method on a challenge over testing in on some of the known datasets is the fact that the ground-truth illuminations for the challenge test images are unknown up until the results have been submitted, which prevents any potential hyperparameter tuning that may be biased.
no code implementations • 9 Nov 2020 • Yanlin Qian, Miaojing Shi, Joni-Kristian Kämäräinen, Jiri Matas
We address the problem of decomposing an image into albedo and shading.
no code implementations • 11 Oct 2020 • Yanlin Qian, Sibo Feng, Kang Qian, Miaofeng Wang
We propose a neural network-based solution for three different tracks of 2nd International Illumination Estimation Challenge (chromaticity. iitp. ru).
3 code implementations • 8 Mar 2020 • Yanlin Qian, Jani Käpylä, Joni-Kristian Kämäräinen, Samu Koskinen, Jiri Matas
The conventional approach is to use a single frame - shot frame - to estimate the scene illumination color.
1 code implementation • 24 Dec 2019 • Huanglin Yu, Ke Chen, Kaiqi Wang, Yanlin Qian, Zhao-Xiang Zhang, Kui Jia
Regressing the illumination of a scene from the representations of object appearances is popularly adopted in computational color constancy.
no code implementations • 2 Dec 2019 • Yanlin Qian, Alan Lukežič, Matej Kristan, Joni-Kristian Kämäräinen, Jiri Matas
In this work, we propose a deep depth-aware long-term tracker that achieves state-of-the-art RGBD tracking performance and is fast to run.
no code implementations • 6 Aug 2019 • Yanlin Qian, Ke Chen, Huanglin Yu
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.
no code implementations • 27 Feb 2019 • Yanlin Qian, Song Yan, Joni-Kristian Kämäräinen, Jiri Matas
In the real world, a scene is usually cast by multiple illuminants and herein we address the problem of spatial illumination estimation.
2 code implementations • CVPR 2019 • Yanlin Qian, Joni-Kristian Kämäräinen, Jarno Nikkanen, Jiri Matas
We propose a novel grayness index for finding gray pixels and demonstrate its effectiveness and efficiency in illumination estimation.
1 code implementation • 21 May 2018 • Wenyan Yang, Yanlin Qian, Francesco Cricri, Lixin Fan, Joni-Kristian Kamarainen
We introduced a high-resolution equirectangular panorama (360-degree, virtual reality) dataset for object detection and propose a multi-projection variant of YOLO detector.
1 code implementation • 22 Mar 2018 • Yanlin Qian, Said Pertuz, Jarno Nikkanen, Joni-Kristian Kämäräinen, Jiri Matas
We present a statistical color constancy method that relies on novel gray pixel detection and mean shift clustering.
no code implementations • ICCV 2017 • Yanlin Qian, Ke Chen, Jarno Nikkanen, Joni-Kristian Kamarainen, Jiri Matas
We introduce a novel formulation of temporal color constancy which considers multiple frames preceding the frame for which illumination is estimated.
no code implementations • 15 Mar 2017 • Dingding Cai, Ke Chen, Yanlin Qian, Joni-Kristian Kämäräinen
Successful fine-grained image classification methods learn subtle details between visually similar (sub-)classes, but the problem becomes significantly more challenging if the details are missing due to low resolution.
no code implementations • 13 Jul 2016 • Yanlin Qian, Ke Chen, Joni-Kristian Kamarainen, Jarno Nikkanen, Jiri Matas
Computational color constancy that requires esti- mation of illuminant colors of images is a fundamental yet active problem in computer vision, which can be formulated into a regression problem.