Visual Perception of Building and Household Vulnerability from Streets

no code implementations • 28 May 2022 • Chaofeng Wang, Sarah Elizabeth Antos, Jessica Grayson Gosling Goldsmith, Luis Miguel Triveno

For that purpose, we create an index, which synthesises the highest possible level of granularity of data at the housing unit and at the household level at the block level, and assess whether the predictions made by our model could be used to approximate vulnerability conditions with a lower budget and in selected areas.

AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results

2 code implementations • 4 Nov 2019 • Kai Zhang, Shuhang Gu, Radu Timofte, Zheng Hui, Xiumei Wang, Xinbo Gao, Dongliang Xiong, Shuai Liu, Ruipeng Gang, Nan Nan, Chenghua Li, Xueyi Zou, Ning Kang, Zhan Wang, Hang Xu, Chaofeng Wang, Zheng Li, Lin-Lin Wang, Jun Shi, Wenyu Sun, Zhiqiang Lang, Jiangtao Nie, Wei Wei, Lei Zhang, Yazhe Niu, Peijin Zhuo, Xiangzhen Kong, Long Sun, Wenhao Wang

The challenge had 3 tracks.

Image Super-Resolution

Building Information Modeling and Classification by Visual Learning At A City Scale

no code implementations • 14 Oct 2019 • Qian Yu, Chaofeng Wang, Barbaros Cetiner, Stella X. Yu, Frank Mckenna, Ertugrul Taciroglu, Kincho H. Law

In the first case, a machine learning-assisted framework, BRAILS, is proposed for city-scale building information modeling.

BIG-bench Machine Learning General Classification

Lightweight Image Super-Resolution with Adaptive Weighted Learning Network

1 code implementation • 4 Apr 2019 • Chaofeng Wang, Zheng Li, Jun Shi

PyTorch code for our paper "Lightweight Image Super-Resolution with Adaptive Weighted Learning Network"

Image Super-Resolution