75 citations · 218 across the 11 of their papers we have counts for
5 papers · 1 filter
Self-supervised Amodal Video Object Segmentation
Jian Yao, Yuxin Hong, Chiyu Wang +6
Amodal perception requires inferring the full shape of an object that is partially occluded. This task is particularly challenging on two levels: (1) it requires more information t…
Single Image Reflection Removal Exploiting Misaligned Training Data and Network Enhancements
Kaixuan Wei, Jiaolong Yang, Ying Fu +2
Removing undesirable reflections from a single image captured through a glass window is of practical importance to visual computing systems. Although state-of-the-art methods can o…
Image Smoothing via Unsupervised Learning
Qingnan Fan, Jiaolong Yang, David Wipf +2
Image smoothing represents a fundamental component of many disparate computer vision and graphics applications. In this paper, we present a unified unsupervised (label-free) learni…
Compressing Neural Networks using the Variational Information Bottleneck
Bin Dai, Chen Zhu, David Wipf
Neural networks can be compressed to reduce memory and computational requirements, or to increase accuracy by facilitating the use of a larger base architecture. In this paper we f…
Image Super-Resolution via Sparse Bayesian Modeling of Natural Images
Haichao Zhang, David Wipf, Yanning Zhang
Image super-resolution (SR) is one of the long-standing and active topics in image processing community. A large body of works for image super resolution formulate the problem with…