26 citations · 61 across the 8 of their papers we have counts for
4 papers · 1 filter
AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning
Ziqi Zhou, Shengshan Hu, Minghui Li +3
Multimodal contrastive learning aims to train a general-purpose feature extractor, such as CLIP, on vast amounts of raw, unlabeled paired image-text data. This can greatly benefit…
Downstream-agnostic Adversarial Examples
Ziqi Zhou, Shengshan Hu, Ruizhi Zhao +4
Self-supervised learning usually uses a large amount of unlabeled data to pre-train an encoder which can be used as a general-purpose feature extractor, such that downstream users…
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples
Shengshan Hu, Junwei Zhang, Wei Liu +5
Point cloud completion, as the upstream procedure of 3D recognition and segmentation, has become an essential part of many tasks such as navigation and scene understanding. While v…
Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer
Shengshan Hu, Xiaogeng Liu, Yechao Zhang +4
While deep face recognition (FR) systems have shown amazing performance in identification and verification, they also arouse privacy concerns for their excessive surveillance on us…