665 citations · 1.3k across the 35 of their papers we have counts for
5 papers · 1 filter
Can machines learn to see without visual databases?
Alessandro Betti, Marco Gori, Stefano Melacci +2
This paper sustains the position that the time has come for thinking of learning machines that conquer visual skills in a truly human-like context, where a few human-like object su…
LUAI Challenge 2021 on Learning to Understand Aerial Images
Gui-Song Xia, Jian Ding, Ming Qian +33
This report summarizes the results of Learning to Understand Aerial Images (LUAI) 2021 challenge held on ICCV 2021, which focuses on object detection and semantic segmentation in a…
Backdoor Learning Curves: Explaining Backdoor Poisoning Beyond Influence Functions
Antonio Emanuele Cinà, Kathrin Grosse, Sebastiano Vascon +4
Backdoor attacks inject poisoning samples during training, with the goal of forcing a machine learning model to output an attacker-chosen class when presented a specific trigger at…
The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers?
Antonio Emanuele Cinà, Sebastiano Vascon, Ambra Demontis +3
One of the most concerning threats for modern AI systems is data poisoning, where the attacker injects maliciously crafted training data to corrupt the system's behavior at test ti…
Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges
Jian Ding, Nan Xue, Gui-Song Xia +8
In the past decade, object detection has achieved significant progress in natural images but not in aerial images, due to the massive variations in the scale and orientation of obj…