28 citations · 49 across the 4 of their papers we have counts for
6 papers
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…
Boundary-Aware Salient Object Detection via Recurrent Two-Stream Guided Refinement Network
Fangting Lin, Chao Yang, Huizhou Li +1
Recent deep learning based salient object detection methods which utilize both saliency and boundary features have achieved remarkable performance. However, most of them ignore the…
Constrained R-CNN: A general image manipulation detection model
Chao Yang, Huizhou Li, Fangting Lin +2
Recently, deep learning-based models have exhibited remarkable performance for image manipulation detection. However, most of them suffer from poor universality of handcrafted or p…
Context-Integrated and Feature-Refined Network for Lightweight Object Parsing
Bin Jiang, Wenxuan Tu, Chao Yang +1
Semantic segmentation for lightweight object parsing is a very challenging task, because both accuracy and efficiency (e.g., execution speed, memory footprint or computational comp…
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…