3 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.LG2021★ 3 cited
DPNAS: Neural Architecture Search for Deep Learning with Differential Privacy
Anda Cheng, Jiaxing Wang, Xi Sheryl Zhang +3
Training deep neural networks (DNNs) for meaningful differential privacy (DP) guarantees severely degrades model utility. In this paper, we demonstrate that the architecture of DNN…
cs.CV2019★ 1 cited
Location-aware Upsampling for Semantic Segmentation
Xiangyu He, Zitao Mo, Qiang Chen +3
Many successful learning targets such as minimizing dice loss and cross-entropy loss have enabled unprecedented breakthroughs in segmentation tasks. Beyond these semantic metrics,…
cs.CV2019
SpatialFlow: Bridging All Tasks for Panoptic Segmentation
Qiang Chen, Anda Cheng, Xiangyu He +2
Object location is fundamental to panoptic segmentation as it is related to all things and stuff in the image scene. Knowing the locations of objects in the image provides clues fo…