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 …
[HTML][HTML] Green learning: Introduction, examples and outlook
CCJ Kuo, AM Madni - Journal of Visual Communication and Image …, 2023 - Elsevier
Rapid advances in artificial intelligence (AI) in the last decade have been largely built upon
the wide applications of deep learning (DL). However, the high carbon footprint yielded by …
the wide applications of deep learning (DL). However, the high carbon footprint yielded by …
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 …
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 …
Maniqa: Multi-dimension attention network for no-reference image quality assessment
Abstract No-Reference Image Quality Assessment (NR-IQA) aims to assess the perceptual
quality of images in accordance with human subjective perception. Unfortunately, existing …
quality of images in accordance with human subjective perception. Unfortunately, existing …
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 …
Quality-aware pre-trained models for blind image quality assessment
Blind image quality assessment (BIQA) aims to automatically evaluate the perceived quality
of a single image, whose performance has been improved by deep learning-based methods …
of a single image, whose performance has been improved by deep learning-based methods …
No-reference image quality assessment via transformers, relative ranking, and self-consistency
Abstract The goal of No-Reference Image Quality Assessment (NR-IQA) is to estimate the
perceptual image quality in accordance with subjective evaluations, it is a complex and …
perceptual image quality in accordance with subjective evaluations, it is a complex and …
Re-iqa: Unsupervised learning for image quality assessment in the wild
Abstract Automatic Perceptual Image Quality Assessment is a challenging problem that
impacts billions of internet, and social media users daily. To advance research in this field …
impacts billions of internet, and social media users daily. To advance research in this field …
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 …