71 citations · 77 across the 3 of their papers we have counts for
5 papers · 1 filter
Studying Bias in GANs through the Lens of Race
Vongani H. Maluleke, Neerja Thakkar, Tim Brooks +5
In this work, we study how the performance and evaluation of generative image models are impacted by the racial composition of their training datasets. By examining and controlling…
Incidents1M: a large-scale dataset of images with natural disasters, damage, and incidents
Ethan Weber, Dim P. Papadopoulos, Agata Lapedriza +3
Natural disasters, such as floods, tornadoes, or wildfires, are increasingly pervasive as the Earth undergoes global warming. It is difficult to predict when and where an incident…
Scaling up instance annotation via label propagation
Dim P. Papadopoulos, Ethan Weber, Antonio Torralba
Manually annotating object segmentation masks is very time-consuming. While interactive segmentation methods offer a more efficient alternative, they become unaffordable at a large…
Detecting natural disasters, damage, and incidents in the wild
Ethan Weber, Nuria Marzo, Dim P. Papadopoulos +5
Responding to natural disasters, such as earthquakes, floods, and wildfires, is a laborious task performed by on-the-ground emergency responders and analysts. Social media has emer…
Building Disaster Damage Assessment in Satellite Imagery with Multi-Temporal Fusion
Ethan Weber, Hassan Kané
Automatic change detection and disaster damage assessment are currently procedures requiring a huge amount of labor and manual work by satellite imagery analysts. In the occurrence…