28 citations · 64 across the 5 of their papers we have counts for
6 papers
One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations
Yiming Zhu, Hongyu Liu, Yibing Song +5
Free-form text prompts allow users to describe their intentions during image manipulation conveniently. Based on the visual latent space of StyleGAN[21] and text embedding space of…
PD-GAN: Probabilistic Diverse GAN for Image Inpainting
Hongyu Liu, Ziyu Wan, Wei Huang +3
We propose PD-GAN, a probabilistic diverse GAN for image inpainting. Given an input image with arbitrary hole regions, PD-GAN produces multiple inpainting results with diverse and…
DeFLOCNet: Deep Image Editing via Flexible Low-level Controls
Hongyu Liu, Ziyu Wan, Wei Huang +5
User-intended visual content fills the hole regions of an input image in the image editing scenario. The coarse low-level inputs, which typically consist of sparse sketch lines and…
Rethinking Image Inpainting via a Mutual Encoder-Decoder with Feature Equalizations
Hongyu Liu, Bin Jiang, Yibing Song +2
Deep encoder-decoder based CNNs have advanced image inpainting methods for hole filling. While existing methods recover structures and textures step-by-step in the hole regions, th…
One-Stage Inpainting with Bilateral Attention and Pyramid Filling Block
Hongyu Liu, Bin Jiang, Wei Huang +1
Recent deep learning based image inpainting methods which utilize contextual information and two-stage architecture have exhibited remarkable performance. However, the two-stage ar…
Coherent Semantic Attention for Image Inpainting
Hongyu Liu, Bin Jiang, Yi Xiao +1
The latest deep learning-based approaches have shown promising results for the challenging task of inpainting missing regions of an image. However, the existing methods often gener…