57 citations · 119 across the 19 of their papers we have counts for
6 papers · 1 filter
T2IW: Joint Text to Image & Watermark Generation
An-An Liu, Guokai Zhang, Yuting Su +3
Recent developments in text-conditioned image generative models have revolutionized the production of realistic results. Unfortunately, this has also led to an increase in privacy…
Variational Label-Correlation Enhancement for Congestion Prediction
Biao Liu, Congyu Qiao, Ning Xu +3
The physical design process of large-scale designs is a time-consuming task, often requiring hours to days to complete, with routing being the most critical and complex step. As th…
Towards Effective Visual Representations for Partial-Label Learning
Shiyu Xia, Jiaqi Lv, Ning Xu +2
Under partial-label learning (PLL) where, for each training instance, only a set of ambiguous candidate labels containing the unknown true label is accessible, contrastive learning…
Learning From Biased Soft Labels
Hua Yuan, Ning Xu, Yu Shi +2
Knowledge distillation has been widely adopted in a variety of tasks and has achieved remarkable successes. Since its inception, many researchers have been intrigued by the dark kn…
Unreliable Partial Label Learning with Recursive Separation
Yu Shi, Ning Xu, Hua Yuan +1
Partial label learning (PLL) is a typical weakly supervised learning problem in which each instance is associated with a candidate label set, and among which only one is true. Howe…
Point Cloud Registration for LiDAR and Photogrammetric Data: a Critical Synthesis and Performance Analysis on Classic and Deep Learning Algorithms
Ningli Xu, Rongjun Qin, Shuang Song
Recent advances in computer vision and deep learning have shown promising performance in estimating rigid/similarity transformation between unregistered point clouds of complex obj…