… Meanwhile, the self-supervised learning aims to learn robust and semantic … self-supervised
learning to against adversarial examples in this paper. Specifically, the self-supervised …

… for self-supervised adversarial learning and … adversarial learning approaches. The results
show that RoCL obtains comparable accuracy to strong supervised adversarial learning …

… In this paper, we take the first step to combine the benefits of both approaches and propose
a self-supervised adversarial training mechanism in the input space. By design, our defense …

… adversarial anomaly detection (DAAD) method which utilizes self-supervised learning along
with an adversarial training … In this paper, we refer to the self-supervised learning method to …

… adversarial training baseline. Moreover, we find that different self-supervised pretrained
models have diverse adversarial … generalize adversarial training (AT) to different self-supervised …

… We propose a self-supervised learning framework for visual odometry (VO) that … and takes
advantage of adversarial learning. Previous methods tackle self-supervised VO as a local …

… Experimental setup: To study the flexibility and efficacy of our proposed self-supervised
framework, we apply DiRA to three recent SOTA self-supervised methods with diverse …

… Adversarial Training This section describes the proposed self-supervised training strategy.
We describe the batch formation for training, then introduce the contrastive learning …

… It’s worth noting that when we discuss adversarial training in our work, we … to train the model
with adversarial selfsupervised learning. First, we show that training selfsupervised learning …

… Self-supervised learning methods construct pretexts to learn representations from … self-supervised
learning. Our method learns representations for vessel segmentation by adversarial …