no code implementations • 7 Feb 2024 • Yuanfang Zhang, Junxuan Li, Kaiqing Luo, Yiying Yang, Jiayi Han, Nian Liu, Denghui Qin, Peng Han, Chengpei Xu
Extensive experiments demonstrate that by leveraging V2V communication, the SSC performance can be increased by 8. 3% on geometric metric IoU and 6. 0% mIOU.
no code implementations • 6 Dec 2023 • Shunsuke Saito, Gabriel Schwartz, Tomas Simon, Junxuan Li, Giljoo Nam
The fidelity of relighting is bounded by both geometry and appearance representations.
1 code implementation • CVPR 2023 • Ziang Cheng, Junxuan Li, Hongdong Li
Our system recovers scene geometry and reflectance using only multi-view images captured by a smartphone.
no code implementations • CVPR 2023 • Junxuan Li, Shunsuke Saito, Tomas Simon, Stephen Lombardi, Hongdong Li, Jason Saragih
However, modeling the geometric and appearance interactions of glasses and the face of virtual representations of humans is challenging.
1 code implementation • 16 Jul 2022 • Junxuan Li, Hongdong Li
This paper tackles the task of uncalibrated photometric stereo for 3D object reconstruction, where both the object shape, object reflectance, and lighting directions are unknown.
1 code implementation • CVPR 2022 • Junxuan Li, Hongdong Li
This network is able to leverage the observed photometric variance and shadows on the surface, and recover both surface shape and general non-Lambertian reflectance.
no code implementations • 29 Sep 2021 • Junxuan Li, Hongdong Li
This paper addresses a challenging Photometric-Stereo problem where the object to be reconstructed has unknown, non-Lambertian, and possibly spatially-varying surface materials.
no code implementations • 29 Sep 2021 • Junxuan Li, Yujiao Shi, Hongdong Li
It encodes a complete light-field (\ie, lumigraph) therefore allows one to freely roam in the space and view the scene from any location in any direction.
no code implementations • CVPR 2021 • Junxuan Li, Hongdong Li, Yasuyuki Matsushita
We propose a method for estimating high-definition spatially-varying lighting, reflectance, and geometry of a scene from 360deg stereo images.
no code implementations • 20 Apr 2021 • Junxuan Li, Hongdong Li, Yasuyuki Matsushita
We propose a method for estimating high-definition spatially-varying lighting, reflectance, and geometry of a scene from 360$^{\circ}$ stereo images.
no code implementations • CVPR 2019 • Junxuan Li, Antonio Robles-Kelly, Shaodi You, Yasuyuki Matsushita
Photometric stereo estimates the surface normal given a set of images acquired under different illumination conditions.
no code implementations • 14 Nov 2018 • Junxuan Li, Yung-wen Liu, Yuting Jia, Yifei Ren, Jay Nanduri
Using partially mature data directly for predictive modeling in an uncertain probabilistic decision environment would lead to significant inaccuracy on risk decision-making.
no code implementations • 3 Oct 2018 • Junxuan Li, Yung-wen Liu, Yuting Jia, Jay Nanduri
While E-commerce has been growing explosively and online shopping has become popular and even dominant in the present era, online transaction fraud control has drawn considerable attention in business practice and academic research.
no code implementations • 8 Dec 2017 • Junxuan Li, ShaoDi You, Antonio Robles-Kelly
Moreover, the non-linearity in deep nets, often achieved by a rectifier unit, is here cast as a convolution in the frequency domain.
no code implementations • 4 Oct 2017 • Junxuan Li
Convolutional neural networks (CNNs) have been widely used over many areas in compute vision.