3 citations · 5 across the 11 of their papers we have counts for
7 papers · 1 filter
Artificial Intelligence for Geometry-Based Feature Extraction, Analysis and Synthesis in Artistic Images: A Survey
Mridula Vijendran, Jingjing Deng, Shuang Chen +2
Artificial Intelligence significantly enhances the visual art industry by analyzing, identifying and generating digitized artistic images. This review highlights the substantial be…
SEM-Net: Efficient Pixel Modelling for image inpainting with Spatially Enhanced SSM
Shuang Chen, Haozheng Zhang, Amir Atapour-Abarghouei +1
Image inpainting aims to repair a partially damaged image based on the information from known regions of the images. \revise{Achieving semantically plausible inpainting results is…
One-Index Vector Quantization Based Adversarial Attack on Image Classification
Haiju Fan, Xiaona Qin, Shuang Chen +2
To improve storage and transmission, images are generally compressed. Vector quantization (VQ) is a popular compression method as it has a high compression ratio that suppresses ot…
MxT: Mamba x Transformer for Image Inpainting
Shuang Chen, Amir Atapour-Abarghouei, Haozheng Zhang +1
Image inpainting, or image completion, is a crucial task in computer vision that aims to restore missing or damaged regions of images with semantically coherent content. This techn…
Depth-Aware Endoscopic Video Inpainting
Francis Xiatian Zhang, Shuang Chen, Xianghua Xie +1
Video inpainting fills in corrupted video content with plausible replacements. While recent advances in endoscopic video inpainting have shown potential for enhancing the quality o…
Geometric Features Enhanced Human-Object Interaction Detection
Manli Zhu, Edmond S. L. Ho, Shuang Chen +2
Cameras are essential vision instruments to capture images for pattern detection and measurement. Human-object interaction (HOI) detection is one of the most popular pattern detect…
HINT: High-quality INPainting Transformer with Mask-Aware Encoding and Enhanced Attention
Shuang Chen, Amir Atapour-Abarghouei, Hubert P. H. Shum
Existing image inpainting methods leverage convolution-based downsampling approaches to reduce spatial dimensions. This may result in information loss from corrupted images where t…