42 citations · 43 across the 5 of their papers we have counts for
5 papers
SimpSON: Simplifying Photo Cleanup with Single-Click Distracting Object Segmentation Network
Chuong Huynh, Yuqian Zhou, Zhe Lin +4
In photo editing, it is common practice to remove visual distractions to improve the overall image quality and highlight the primary subject. However, manually selecting and removi…
Image as Set of Points
Xu Ma, Yuqian Zhou, Huan Wang +4
What is an image and how to extract latent features? Convolutional Networks (ConvNets) consider an image as organized pixels in a rectangular shape and extract features via convolu…
Perceptual Artifacts Localization for Inpainting
Lingzhi Zhang, Yuqian Zhou, Connelly Barnes +4
Image inpainting is an essential task for multiple practical applications like object removal and image editing. Deep GAN-based models greatly improve the inpainting performance in…
Keys to Better Image Inpainting: Structure and Texture Go Hand in Hand
Jitesh Jain, Yuqian Zhou, Ning Yu +1
Deep image inpainting has made impressive progress with recent advances in image generation and processing algorithms. We claim that the performance of inpainting algorithms can be…
Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining
Yiqun Mei, Yuchen Fan, Yuqian Zhou +3
Deep convolution-based single image super-resolution (SISR) networks embrace the benefits of learning from large-scale external image resources for local recovery, yet most existin…