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20202024
most citedTowards Robust Neural Networks via Orthogonal Diversity

10 citations · 32 across the 13 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model

Kun Fang, Zuopeng Yang, Haibo Hu +3

Out-of-Distribution (OoD) detection aims to justify whether a given sample is from the training distribution of the classifier-under-protection, i.e., In-Distribution (InD), or fro…

cs.CV2022★ 3 cited

Efficient Generalization Improvement Guided by Random Weight Perturbation

Tao Li, Weihao Yan, Zehao Lei +4

To fully uncover the great potential of deep neural networks (DNNs), various learning algorithms have been developed to improve the model's generalization ability. Recently, sharpn…

cs.CV2022

Online LiDAR-Camera Extrinsic Parameters Self-checking

Pengjin Wei, Guohang Yan, Yikang Li +3

With the development of neural networks and the increasing popularity of automatic driving, the calibration of the LiDAR and the camera has attracted more and more attention. This…

cs.CV2022

CROON: Automatic Multi-LiDAR Calibration and Refinement Method in Road Scene

Pengjin Wei, Guohang Yan, Yikang Li +4

Sensor-based environmental perception is a crucial part of the autonomous driving system. In order to get an excellent perception of the surrounding environment, an intelligent sys…

cs.CV2020★ 10 cited

Towards Robust Neural Networks via Orthogonal Diversity

Kun Fang, Qinghua Tao, Yingwen Wu +5

Deep Neural Networks (DNNs) are vulnerable to invisible perturbations on the images generated by adversarial attacks, which raises researches on the adversarial robustness of DNNs.…