This paper proposes a fundamental answer to a frequently asked question in multimedia evaluation and data set creation: Do artifacts from perceptual ...
As a note, perceptual compression has also proved useful for improv- ing models' robustness against adversarial example-signals that are intentionally made ...
Perceptual compression is actually not harmful but contributes to a significant reduction of complexity of the machine learning process.
As a note, perceptual compression has also proved useful for improv- ing models' robustness against adversarial example-signals that are intentionally made ...
Aug 6, 2020 · This paper proposes a fundamental answer to a frequently asked question in multimedia evaluation and data set creation: Do artifacts from ...
Deep gradient compression would highly increase the bandwidth utilization and speed up the training process but hard to implement on ring structure. In this ...
In this repository, we release code and data for conducting perceptual compression while maintaining, or sometimes even improving, overall performance.
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2020 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) / , 2020, p.219-224 ,. On the Impact of Perceptual Compression on Deep ...
Nov 10, 2023 · The main objective of this paper is to study the perceptual impact of several image quality metrics that can be used in the loss function of the training ...
Aug 29, 2024 · For example, images generated using CGH often display ringing patterns, quantization noise, and speckle artifacts that are direct consequences ...