no code implementations • ECCV 2020 • Xuejian Rong, Denis Demandolx, Kevin Matzen, Priyam Chatterjee, YingLi Tian
As a result, imaging pipelines often rely on computational photography to improve SNR by fusing multiple short exposures.
no code implementations • 11 Oct 2022 • Peiye Zhuang, Jia-Bin Huang, Ayush Saraf, Xuejian Rong, Changil Kim, Denis Demandolx
Image composition aims to blend multiple objects to form a harmonized image.
no code implementations • CVPR 2022 • Xuejian Rong, Jia-Bin Huang, Ayush Saraf, Changil Kim, Johannes Kopf
We present a simple but effective technique to boost the rendering quality, which can be easily integrated with most view synthesis methods.
1 code implementation • CVPR 2021 • Johannes Kopf, Xuejian Rong, Jia-Bin Huang
We present an algorithm for estimating consistent dense depth maps and camera poses from a monocular video.
no code implementations • 26 Apr 2020 • Hai-Yan Wang, Xuejian Rong, Liang Yang, Jinglun Feng, Jizhong Xiao, YingLi Tian
The deficiency of 3D segmentation labels is one of the main obstacles to effective point cloud segmentation, especially for scenes in the wild with varieties of different objects.
no code implementations • NeurIPS 2019 • Benjamin Planche, Xuejian Rong, Ziyan Wu, Srikrishna Karanam, Harald Kosch, YingLi Tian, Jan Ernst, Andreas Hutter
We present a method to incrementally generate complete 2D or 3D scenes with the following properties: (a) it is globally consistent at each step according to a learned scene prior, (b) real observations of a scene can be incorporated while observing global consistency, (c) unobserved regions can be hallucinated locally in consistence with previous observations, hallucinations and global priors, and (d) hallucinations are statistical in nature, i. e., different scenes can be generated from the same observations.
no code implementations • CVPR 2017 • Xuejian Rong, Chucai Yi, YingLi Tian
Text instance as one category of self-described objects provides valuable information for understanding and describing cluttered scenes.