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20132026
most citedInvisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks

226 citations · 1.6k across the 138 of their papers we have counts for

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Showing 2020 · cs.CVShow all

7 papers · 2 filters

cs.CV2020★ 23 cited

Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration

Bo Li, Wiro J. Niessen, Stefan Klein +4

This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this me…

cs.CV2020★ 1 cited

Learning unbiased group-wise registration (LUGR) and joint segmentation: evaluation on longitudinal diffusion MRI

Bo Li, Wiro J. Niessen, Stefan Klein +3

Analysis of longitudinal changes in imaging studies often involves both segmentation of structures of interest and registration of multiple timeframes. The accuracy of such analysi…

cs.CV2020★ 36 cited

Rethinking Distributional Matching Based Domain Adaptation

Bo Li, Yezhen Wang, Tong Che +6

Domain adaptation (DA) is a technique that transfers predictive models trained on a labeled source domain to an unlabeled target domain, with the core difficulty of resolving distr…

cs.CV2020★ 4 cited

GAPS: Generator for Automatic Polynomial Solvers

Bo Li, Viktor Larsson

Minimal problems in computer vision raise the demand of generating efficient automatic solvers for polynomial equation systems. Given a polynomial system repeated with different co…

cs.CV2020★ 1 cited

Multi-Task Learning Enhanced Single Image De-Raining

Yulong Fan, Rong Chen, Bo Li

Rain removal in images is an important task in computer vision filed and attracting attentions of more and more people. In this paper, we address a non-trivial issue of removing vi…

cs.CV2020★ 4 cited

MADAN: Multi-source Adversarial Domain Aggregation Network for Domain Adaptation

Sicheng Zhao, Bo Li, Xiangyu Yue +2

Domain adaptation aims to learn a transferable model to bridge the domain shift between one labeled source domain and another sparsely labeled or unlabeled target domain. Since the…

cs.CV2020★ 6 cited

Sparse Black-box Video Attack with Reinforcement Learning

Xingxing Wei, Huanqian Yan, Bo Li

Adversarial attacks on video recognition models have been explored recently. However, most existing works treat each video frame equally and ignore their temporal interactions. To…