69 citations · 510 across the 49 of their papers we have counts for
5 papers · 2 filters
Hiding Faces in Plain Sight: Disrupting AI Face Synthesis with Adversarial Perturbations
Yuezun Li, Xin Yang, Baoyuan Wu +1
Recent years have seen fast development in synthesizing realistic human faces using AI technologies. Such fake faces can be weaponized to cause negative personal and social impact.…
Exact Adversarial Attack to Image Captioning via Structured Output Learning with Latent Variables
Yan Xu, Baoyuan Wu, Fumin Shen +4
In this work, we study the robustness of a CNN+RNN based image captioning system being subjected to adversarial noises. We propose to fool an image captioning system to generate so…
Efficient Decision-based Black-box Adversarial Attacks on Face Recognition
Yinpeng Dong, Hang Su, Baoyuan Wu +4
Face recognition has obtained remarkable progress in recent years due to the great improvement of deep convolutional neural networks (CNNs). However, deep CNNs are vulnerable to ad…
Target-Aware Deep Tracking
Xin Li, Chao Ma, Baoyuan Wu +2
Existing deep trackers mainly use convolutional neural networks pre-trained for generic object recognition task for representations. Despite demonstrated successes for numerous vis…
Tencent ML-Images: A Large-Scale Multi-Label Image Database for Visual Representation Learning
Baoyuan Wu, Weidong Chen, Yanbo Fan +4
In existing visual representation learning tasks, deep convolutional neural networks (CNNs) are often trained on images annotated with single tags, such as ImageNet. However, a sin…