Visual Signal Assessment, Analysis and Enhancement for Low-resolution or Varying-illumination Environment

Weisi Lin
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Abstract

More often than not, practical application scenarios call for systems to be capable of dealing with input visual signals with low resolution/quality or environmental illumination. This talk will introduce related recent research in super-resolution reconstruction, signal quality assessment, content enhancement, and person re-identification for low-resolution or varying illumination. We will also discuss possible new research attempts to advance the relevant techniques.
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低分辨率或变照度环境下的视觉信号评估、分析与增强
通常情况下,实际应用场景要求系统能够处理低分辨率/质量或环境照明的输入视觉信号。本讲座将介绍超分辨率重建、信号质量评估、内容增强、低分辨率或变光照下的人再识别等方面的最新研究成果。我们还将讨论可能的新研究尝试,以推进相关技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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In-training Restoration Models Matter: Data Augmentation for Degraded-reference Image Quality Assessment Unlocking the Potential of Disentangled Representation for Robust Media Understanding Visual Signal Assessment, Analysis and Enhancement for Low-resolution or Varying-illumination Environment Advances of Computational Imaging on Mobile Phones Proceedings of the 2nd International Workshop on Robust Understanding of Low-quality Multimedia Data: Unitive Enhancement, Analysis and Evaluation
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