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most citedOne Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection Models

63 citations · 63 across the 1 of their papers we have counts for

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cs.CV2019

Attention Control with Metric Learning Alignment for Image Set-based Recognition

Xiaofeng Liu, Zhenhua Guo, Jane You +1

This paper considers the problem of image set-based face verification and identification. Unlike traditional single sample (an image or a video) setting, this situation assumes the…

cs.CV2019

Dependency-aware Attention Control for Unconstrained Face Recognition with Image Sets

Xiaofeng Liu, B. V. K Vijaya Kumar, Chao Yang +2

This paper targets the problem of image set-based face verification and identification. Unlike traditional single media (an image or video) setting, we encounter a set of heterogen…

cs.CV2018

Simultaneous Edge Alignment and Learning

Zhiding Yu, Weiyang Liu, Yang Zou +4

Edge detection is among the most fundamental vision problems for its role in perceptual grouping and its wide applications. Recent advances in representation learning have led to c…

cs.CV2018

Towards Multifocal Displays with Dense Focal Stacks

Jen-Hao Rick Chang, B. V. K. Vijaya Kumar, Aswin C. Sankaranarayanan

We present a virtual reality display that is capable of generating a dense collection of depth/focal planes. This is achieved by driving a focus-tunable lens to sweep a range of fo…

cs.CV201763 cited

One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection Models

J. H. Rick Chang, Chun-Liang Li, Barnabas Poczos +2

While deep learning methods have achieved state-of-the-art performance in many challenging inverse problems like image inpainting and super-resolution, they invariably involve prob…