15 citations · 40 across the 3 of their papers we have counts for
5 papers
WeakM3D: Towards Weakly Supervised Monocular 3D Object Detection
Liang Peng, Senbo Yan, Boxi Wu +3
Monocular 3D object detection is one of the most challenging tasks in 3D scene understanding. Due to the ill-posed nature of monocular imagery, existing monocular 3D detection meth…
Attacking Adversarial Attacks as A Defense
Boxi Wu, Heng Pan, Li Shen +6
It is well known that adversarial attacks can fool deep neural networks with imperceptible perturbations. Although adversarial training significantly improves model robustness, fai…
Do Wider Neural Networks Really Help Adversarial Robustness?
Boxi Wu, Jinghui Chen, Deng Cai +2
Adversarial training is a powerful type of defense against adversarial examples. Previous empirical results suggest that adversarial training requires wider networks for better per…
Correlation Maximized Structural Similarity Loss for Semantic Segmentation
Shuai Zhao, Boxi Wu, Wenqing Chu +2
Most semantic segmentation models treat semantic segmentation as a pixel-wise classification task and use a pixel-wise classification error as their optimization criterions. Howeve…
Improving Semantic Segmentation via Dilated Affinity
Boxi Wu, Shuai Zhao, Wenqing Chu +2
Introducing explicit constraints on the structural predictions has been an effective way to improve the performance of semantic segmentation models. Existing methods are mainly bas…