408 citations · 1.1k across the 11 of their papers we have counts for
11 papers
Incremental Cross-view Mutual Distillation for Self-supervised Medical CT Synthesis
Chaowei Fang, Liang Wang, Dingwen Zhang +3
Due to the constraints of the imaging device and high cost in operation time, computer tomography (CT) scans are usually acquired with low intra-slice resolution. Improving the int…
MetaKernel: Learning Variational Random Features with Limited Labels
Yingjun Du, Haoliang Sun, Xiantong Zhen +4
Few-shot learning deals with the fundamental and challenging problem of learning from a few annotated samples, while being able to generalize well on new tasks. The crux of few-sho…
Temporal Modulation Network for Controllable Space-Time Video Super-Resolution
Gang Xu, Jun Xu, Zhen Li +3
Space-time video super-resolution (STVSR) aims to increase the spatial and temporal resolutions of low-resolution and low-frame-rate videos. Recently, deformable convolution based…
MobileSal: Extremely Efficient RGB-D Salient Object Detection
Yu-Huan Wu, Yun Liu, Jun Xu +3
The high computational cost of neural networks has prevented recent successes in RGB-D salient object detection (SOD) from benefiting real-world applications. Hence, this paper int…
Learning to Learn with Variational Information Bottleneck for Domain Generalization
Yingjun Du, Jun Xu, Huan Xiong +4
Domain generalization models learn to generalize to previously unseen domains, but suffer from prediction uncertainty and domain shift. In this paper, we address both problems. We…
Interactive Knowledge Distillation
Shipeng Fu, Zhen Li, Jun Xu +3
Knowledge distillation is a standard teacher-student learning framework to train a light-weight student network under the guidance of a well-trained large teacher network. As an ef…