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What Is It Like Down There? Generating Dense Ground-Level Views and
  Image Features From Overhead Imagery Using Conditional Generative Adversarial
  Networks

What Is It Like Down There? Generating Dense Ground-Level Views and Image Features From Overhead Imagery Using Conditional Generative Adversarial Networks

13 June 2018
XueQing Deng
Yi Zhu
Shawn D. Newsam
    GAN
ArXivPDFHTML

Papers citing "What Is It Like Down There? Generating Dense Ground-Level Views and Image Features From Overhead Imagery Using Conditional Generative Adversarial Networks"

6 / 6 papers shown
Title
Bird's-Eye View to Street-View: A Survey
Bird's-Eye View to Street-View: A Survey
Khawlah Bajbaa
Muhammad Usman
Saeed Anwar
Ibrahim Radwan
Abdul Bais
33
1
0
14 May 2024
Semantic-aware Network for Aerial-to-Ground Image Synthesis
Semantic-aware Network for Aerial-to-Ground Image Synthesis
J. Jang
Taeyong Song
Kwanghoon Sohn
GAN
21
2
0
14 Aug 2023
Unsupervised Discovery of Semantic Concepts in Satellite Imagery with
  Style-based Wavelet-driven Generative Models
Unsupervised Discovery of Semantic Concepts in Satellite Imagery with Style-based Wavelet-driven Generative Models
Nikos Kostagiolas
M. Nicolaou
Yannis Panagakis
GAN
18
2
0
03 Aug 2022
Towards a Collective Agenda on AI for Earth Science Data Analysis
Towards a Collective Agenda on AI for Earth Science Data Analysis
D. Tuia
R. Roscher
Jan Dirk Wegner
Nathan Jacobs
Xiaoxiang Zhu
Gustau Camps-Valls
AI4CE
39
68
0
11 Apr 2021
Learning a Dynamic Map of Visual Appearance
Learning a Dynamic Map of Visual Appearance
Tawfiq Salem
Scott Workman
Nathan Jacobs
3DH
24
26
0
29 Dec 2020
Scale Aware Adaptation for Land-Cover Classification in Remote Sensing
  Imagery
Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery
XueQing Deng
Yi Zhu
Yuxin Tian
Shawn D. Newsam
21
23
0
08 Dec 2020
1