6 accepted papers
Deep-learning-based face recognition (FR) systems are susceptible to adversarial examples in both digital and physical domains. Physical attacks present a greater threat to deployed systems as adversaries can easily access the input channel, allowing them to provide malicious inputs to impersonate a…
As deepfake and adversarial attacks evolve, facial recognition systems are encountering increasingly diverse threats. Most existing face liveness detection algorithms focus on single tasks, like spoofing or deepfake attack detection. The corresponding datasets have limited coverage of attack methods…
In real-world scenarios, many robotic manipulation tasks are hindered by occlusions and limited fields of view, posing significant challenges for passive observation-based models that rely on fixed or wrist-mounted cameras. In this letter, we investigate the problem of robotic manipulation under lim
Flexible sensors for joint angle measurement play a crucial role in various human-robot interaction applications. In previous studies, sensors with various sensing mechanisms have been developed. Among them, optical waveguide sensors exhibit high resistance to environmental factors (such as temperat…
Face Recognition (FR) systems can suffer from physical (i.e., print photo) and digital (i.e., DeepFake) attacks. However, previous related work rarely considers both situations at the same time. This implies the deployment of multiple models and thus more computational burden. The main reasons for t…
It is of great importance to improve the performance of soft bending actuators with simpler control laws. Considering that the velocity information of soft actuators cannot be measured by conventional sensors due to a contradiction between the soft body and the rigid state, this letter addresses a r