305 citations · 1.1k across the 8 of their papers we have counts for
8 papers
OSS Mentor A framework for improving developers contributions via deep reinforcement learning
Jiakuan Fan, Haoyue Wang, Wei Wang +2
In open source project governance, there has been a lot of concern about how to measure developers' contributions. However, extremely sparse work has focused on enabling developers…
PVNAS: 3D Neural Architecture Search with Point-Voxel Convolution
Zhijian Liu, Haotian Tang, Shengyu Zhao +2
3D neural networks are widely used in real-world applications (e.g., AR/VR headsets, self-driving cars). They are required to be fast and accurate; however, limited hardware resour…
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng +4
Numerous task-specific variants of conditional generative adversarial networks have been developed for image completion. Yet, a serious limitation remains that all existing algorit…
Differentiable Augmentation for Data-Efficient GAN Training
Shengyu Zhao, Zhijian Liu, Ji Lin +2
The performance of generative adversarial networks (GANs) heavily deteriorates given a limited amount of training data. This is mainly because the discriminator is memorizing the e…
MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask
Shengyu Zhao, Yilun Sheng, Yue Dong +2
Feature warping is a core technique in optical flow estimation; however, the ambiguity caused by occluded areas during warping is a major problem that remains unsolved. In this pap…
Recursive Cascaded Networks for Unsupervised Medical Image Registration
Shengyu Zhao, Yue Dong, Eric I-Chao Chang +1
We present recursive cascaded networks, a general architecture that enables learning deep cascades, for deformable image registration. The proposed architecture is simple in design…
Unsupervised 3D End-to-End Medical Image Registration with Volume Tweening Network
Shengyu Zhao, Tingfung Lau, Ji Luo +2
3D medical image registration is of great clinical importance. However, supervised learning methods require a large amount of accurately annotated corresponding control points (or…
Characterization of Group-Strategyproof Mechanisms for Facility Location in Strictly Convex Space
Pingzhong Tang, Dingli Yu, Shengyu Zhao
We characterize the class of group-strategyproof mechanisms for the single facility location game in any unconstrained strictly convex space. A mechanism is \emph{group-strategypro…