3 accepted papers
Saliency maps play a major role in understanding the decision-making process of 3D models by illustrating the importance of individual points from the input to model predictions. However, saliency maps typically suffer from inaccuracies due to not considering the potential classification of contribu…
3D object tracking has become a popular research topic because of its broad application prospects. However, it remains a challenging task to advance the trustworthiness of deep trackers, caused by the complex network structure of black-box models. In this paper, a local explanation method for 3D obj…
It is well-recognized that 3D visual tasks based on deep neural networks are vulnerable to adversarial attacks. Existing methods to generate adversarial examples are mainly developed from injecting imperceptible perturbations into the inputs. However, aggressive characteristic of geometric transform…