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Found 2 papers, 0 papers with code
Re-designing cities with conditional adversarial networks
This paper introduces a conditional generative adversarial network to redesign a street-level image of urban scenes by generating 1) an urban intervention policy, 2) an attention map that localises where intervention is needed, 3) a high-resolution street-level image (1024 X 1024 or 1536 X1536) after implementing the intervention.
Generative Adversarial Network
Image-to-Image Translation
+2
CyclingNet: Detecting cycling near misses from video streams in complex urban scenes with deep learning
Cycling is a promising sustainable mode for commuting and leisure in cities, however, the fear of getting hit or fall reduces its wide expansion as a commuting mode.
