A survey on deep geometry learning: From a representation perspective Tập 6 Số 2 - Trang 113-133 - 2020
Yanfeng Xiao, Yuekun Lai, Fang-Lue Zhang, Chunpeng Li, Lin Gao
AbstractResearchers have achieved great success in dealing with 2D images using
deep learning. In recent years, 3D computer vision and geometry deep learning
have gained ever more attention. Many advanced techniques for 3D shapes have
been proposed for different applications. Unlike 2D images, which can be
uniformly represented by a regular grid of pixels, 3D shapes have various
representations, s... hiện toàn bộ
Saliency-based image correction for colorblind patients - 2020
Jinjiang Li, Xiaomei Feng, Hui Fan
AbstractImproper functioning, or lack, of human cone cells leads to vision
defects, making it impossible for affected persons to distinguish certain
colors. Colorblind persons have color perception, but their ability to capture
color information differs from that of normal people: colorblind and normal
people perceive the same image differently. It is necessary to devise solutions
to help persons ... hiện toàn bộ
Learning conditional photometric stereo with high-resolution features Tập 8 Số 1 - Trang 105-118 - 2022
Yakun Ju, Yuxin Peng, Muwei Jian, Feng Gao, Junyu Dong
AbstractPhotometric stereo aims to reconstruct 3D geometry by recovering the
dense surface orientation of a 3D object from multiple images under differing
illumination. Traditional methods normally adopt simplified reflectance models
to make the surface orientation computable. However, the real reflectances of
surfaces greatly limit applicability of such methods to real-world objects.
While deep n... hiện toàn bộ
Learning to assess visual aesthetics of food images - 2021
Kekai Sheng, Weiming Dong, Haibin Huang, Menglei Chai, Yong Zhang, Chongyang Ma, Bao Gang Hu
AbstractDistinguishing aesthetically pleasing food photos from others is an
important visual analysis task for social media and ranking systems related to
food. Nevertheless, aesthetic assessment of food images remains a challenging
and relatively unexplored task, largely due to the lack of related food image
datasets and practical knowledge. Thus, we present the Gourmet Photography
Dataset (GPD),... hiện toàn bộ
Component SPD matrices: A low-dimensional discriminative data descriptor for image set classification Tập 4 Số 3 - Trang 245-252 - 2018
Kaixuan Chen, Xiao-Jun Wu
Abstract In pattern recognition, the task of image set classification has often
been performed by representing data using symmetric positive definite (SPD)
matrices, in conjunction with the metric of the resulting Riemannian manifold.
In this paper, we propose a new data representation framework for image sets
which we call component symmetric positive definite representation (CSPD).
Firstly, we o... hiện toàn bộ