Zobrazeno 1 - 10
of 82
pro vyhledávání: '"Bampis, Christos G."'
We describe a search-free resizing framework that can further improve the rate-distortion tradeoff of recent learned image compression models. Our approach is simple: compose a pair of differentiable downsampling/upsampling layers that sandwich a neu
Externí odkaz:
http://arxiv.org/abs/2204.12022
Publikováno v:
In Signal Processing: Image Communication October 2024 128
Staircase-like contours introduced to a video by quantization in flat areas, commonly known as banding, have been a long-standing problem in both video processing and quality assessment communities. The fact that even a relatively small change of the
Externí odkaz:
http://arxiv.org/abs/2202.11038
The layers of convolutional neural networks (CNNs) can be used to alter the resolution of their inputs, but the scaling factors are limited to integer values. However, in many image and video processing applications, the ability to resize by a fracti
Externí odkaz:
http://arxiv.org/abs/2105.09999
Autor:
Lee, Dae Yeol, Paul, Somdyuti, Bampis, Christos G., Ko, Hyunsuk, Kim, Jongho, Jeong, Se Yoon, Homan, Blake, Bovik, Alan C.
Video dimensions are continuously increasing to provide more realistic and immersive experiences to global streaming and social media viewers. However, increments in video parameters such as spatial resolution and frame rate are inevitably associated
Externí odkaz:
http://arxiv.org/abs/2102.00088
Measuring the quality of digital videos viewed by human observers has become a common practice in numerous multimedia applications, such as adaptive video streaming, quality monitoring, and other digital TV applications. Here we explore a significant
Externí odkaz:
http://arxiv.org/abs/2009.11203
Mean squared error (MSE) and $\ell_p$ norms have largely dominated the measurement of loss in neural networks due to their simplicity and analytical properties. However, when used to assess visual information loss, these simple norms are not highly c
Externí odkaz:
http://arxiv.org/abs/2007.02711
Autor:
Yu, Xiangxu, Birkbeck, Neil, Wang, Yilin, Bampis, Christos G., Adsumilli, Balu, Bovik, Alan C.
Over the past decade, the online video industry has greatly expanded the volume of visual data that is streamed and shared over the Internet. Moreover, because of the increasing ease of video capture, many millions of consumers create and upload larg
Externí odkaz:
http://arxiv.org/abs/2004.02943
In a subjective experiment to evaluate the perceptual audiovisual quality of multimedia and television services, raw opinion scores collected from test subjects are often noisy and unreliable. To produce the final mean opinion scores (MOS), recommend
Externí odkaz:
http://arxiv.org/abs/2004.02067
The use of $\ell_p$ $(p=1,2)$ norms has largely dominated the measurement of loss in neural networks due to their simplicity and analytical properties. However, when used to assess the loss of visual information, these simple norms are not very consi
Externí odkaz:
http://arxiv.org/abs/1910.08845