Image inpainting based on deep learning: A review
X Zhang, D Zhai, T Li, Y Zhou, Y Lin - Information Fusion, 2023 - Elsevier
Image inpainting is an important research direction in the study of computer vision, and is
widely used in image editing and photo inpainting etc. Traditional image inpainting …
widely used in image editing and photo inpainting etc. Traditional image inpainting …
Musiq: Multi-scale image quality transformer
Image quality assessment (IQA) is an important research topic for understanding and
improving visual experience. The current state-of-the-art IQA methods are based on …
improving visual experience. The current state-of-the-art IQA methods are based on …
Deep portrait quality assessment. a NTIRE 2024 challenge survey
This paper reviews the NTIRE 2024 Portrait Quality Assessment Challenge, highlighting the
proposed solutions and results. This challenge aims to obtain an efficient deep neural …
proposed solutions and results. This challenge aims to obtain an efficient deep neural …
Vbench: Comprehensive benchmark suite for video generative models
Video generation has witnessed significant advancements yet evaluating these models
remains a challenge. A comprehensive evaluation benchmark for video generation is …
remains a challenge. A comprehensive evaluation benchmark for video generation is …
Exploring clip for assessing the look and feel of images
Measuring the perception of visual content is a long-standing problem in computer vision.
Many mathematical models have been developed to evaluate the look or quality of an …
Many mathematical models have been developed to evaluate the look or quality of an …
Low-light image and video enhancement using deep learning: A survey
Low-light image enhancement (LLIE) aims at improving the perception or interpretability of
an image captured in an environment with poor illumination. Recent advances in this area …
an image captured in an environment with poor illumination. Recent advances in this area …
Blind image quality assessment via vision-language correspondence: A multitask learning perspective
We aim at advancing blind image quality assessment (BIQA), which predicts the human
perception of image quality without any reference information. We develop a general and …
perception of image quality without any reference information. We develop a general and …
Q-instruct: Improving low-level visual abilities for multi-modality foundation models
Multi-modality large language models (MLLMs) as represented by GPT-4V have introduced
a paradigm shift for visual perception and understanding tasks that a variety of abilities can …
a paradigm shift for visual perception and understanding tasks that a variety of abilities can …
Image quality assessment using contrastive learning
PC Madhusudana, N Birkbeck, Y Wang… - … on Image Processing, 2022 - ieeexplore.ieee.org
We consider the problem of obtaining image quality representations in a self-supervised
manner. We use prediction of distortion type and degree as an auxiliary task to learn …
manner. We use prediction of distortion type and degree as an auxiliary task to learn …
Perceptual image quality assessment with transformers
In this paper, we propose an image quality transformer (IQT) that successfully applies a
transformer architecture to a perceptual full-reference image quality assessment (IQA) task …
transformer architecture to a perceptual full-reference image quality assessment (IQA) task …