106 citations · 514 across the 39 of their papers we have counts for
8 papers · 1 filter
A Survey on Deep Learning for Human Mobility
Massimiliano Luca, Gianni Barlacchi, Bruno Lepri +1
The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The prolifer…
Semantic-Guided Inpainting Network for Complex Urban Scenes Manipulation
Pierfrancesco Ardino, Yahui Liu, Elisa Ricci +2
Manipulating images of complex scenes to reconstruct, insert and/or remove specific object instances is a challenging task. Complex scenes contain multiple semantics and objects, w…
Retrieval Guided Unsupervised Multi-domain Image-to-Image Translation
Raul Gomez, Yahui Liu, Marco De Nadai +3
Image to image translation aims to learn a mapping that transforms an image from one visual domain to another. Recent works assume that images descriptors can be disentangled into…
Describe What to Change: A Text-guided Unsupervised Image-to-Image Translation Approach
Yahui Liu, Marco De Nadai, Deng Cai +4
Manipulating visual attributes of images through human-written text is a very challenging task. On the one hand, models have to learn the manipulation without the ground truth of t…
Uncovering socioeconomic gaps in mobility reduction during the COVID-19 pandemic using location data
Samuel P. Fraiberger, Pablo Astudillo, Lorenzo Candeago +8
Using smartphone location data from Colombia, Mexico, and Indonesia, we investigate how non-pharmaceutical policy interventions intended to mitigate the spread of the COVID-19 pand…
Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks
Gevorg Yeghikyan, Felix L. Opolka, Mirco Nanni +2
A fundamental problem of interest to policy makers, urban planners, and other stakeholders involved in urban development projects is assessing the impact of planning and constructi…