Search Results for author: Alan C. Bovik

Found 38 papers, 16 papers with code

Making Video Quality Assessment Models Sensitive to Frame Rate Distortions

no code implementations21 May 2022 Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, Alan C. Bovik

We consider the problem of capturing distortions arising from changes in frame rate as part of Video Quality Assessment (VQA).

Frame Video Quality Assessment +2

Estimating the Resize Parameter in End-to-end Learned Image Compression

no code implementations26 Apr 2022 Li-Heng Chen, Christos G. Bampis, Zhi Li, Lukáš Krasula, Alan C. Bovik

By conducting extensive experimental tests on existing deep image compression models, we show results that our new resizing parameter estimation framework can provide Bj{\o}ntegaard-Delta rate (BD-rate) improvement of about 10% against leading perceptual quality engines.

Image Compression

Perceptual Quality Assessment of UGC Gaming Videos

no code implementations31 Mar 2022 Xiangxu Yu, Zhengzhong Tu, Neil Birkbeck, Yilin Wang, Balu Adsumilli, Alan C. Bovik

In recent years, with the vigorous development of the video game industry, the proportion of gaming videos on major video websites like YouTube has dramatically increased.

Video Quality Assessment Visual Question Answering +1

Foveation-based Deep Video Compression without Motion Search

no code implementations30 Mar 2022 Meixu Chen, Richard Webb, Alan C. Bovik

In our learning based approach, we implement foveation by introducing a Foveation Generator Unit (FGU) that generates foveation masks which direct the allocation of bits, significantly increasing compression efficiency while making it possible to retain an impression of little to no additional visual loss given an appropriate viewing geometry.

Foveation motion prediction +1

Subjective and Objective Analysis of Streamed Gaming Videos

no code implementations24 Mar 2022 Xiangxu Yu, Zhenqiang Ying, Neil Birkbeck, Yilin Wang, Balu Adsumilli, Alan C. Bovik

A number of studies have been directed towards understanding the perceptual characteristics of professionally generated gaming videos arising in gaming video streaming, online gaming, and cloud gaming.

Video Quality Assessment Visual Question Answering +1

FUNQUE: Fusion of Unified Quality Evaluators

1 code implementation23 Feb 2022 Abhinau K. Venkataramanan, Cosmin Stejerean, Alan C. Bovik

Fusion-based quality assessment has emerged as a powerful method for developing high-performance quality models from quality models that individually achieve lower performances.


FAVER: Blind Quality Prediction of Variable Frame Rate Videos

1 code implementation5 Jan 2022 Qi Zheng, Zhengzhong Tu, Pavan C. Madhusudana, Xiaoyang Zeng, Alan C. Bovik, Yibo Fan

Video quality assessment (VQA) remains an important and challenging problem that affects many applications at the widest scales.

Frame Video Quality Assessment +2

High Frame Rate Video Quality Assessment using VMAF and Entropic Differences

no code implementations27 Sep 2021 Pavan C Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, Alan C. Bovik

In this work we address the problem of frame rate dependent Video Quality Assessment (VQA) when the videos to be compared have different frame rate and compression factor.

Frame Video Quality Assessment +2

Convolutional Block Design for Learned Fractional Downsampling

no code implementations20 May 2021 Li-Heng Chen, Christos G. Bampis, Zhi Li, Chao Chen, Alan C. Bovik

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.

SSIM Video Compression

Space-Time Video Regularity and Visual Fidelity: Compression, Resolution and Frame Rate Adaptation

no code implementations31 Mar 2021 Dae Yeol Lee, Hyunsuk Ko, Jongho Kim, Alan C. Bovik

As a stringent test of the new model, we apply it to the difficult problem of predicting the quality of videos subjected not only to compression, but also to downsampling in space and/or time.


Regression or Classification? New Methods to Evaluate No-Reference Picture and Video Quality Models

no code implementations30 Jan 2021 Zhengzhong Tu, Chia-Ju Chen, Li-Heng Chen, Yilin Wang, Neil Birkbeck, Balu Adsumilli, Alan C. Bovik

Video and image quality assessment has long been projected as a regression problem, which requires predicting a continuous quality score given an input stimulus.

General Classification Image Quality Assessment

On the Space-Time Statistics of Motion Pictures

no code implementations29 Jan 2021 Dae Yeol Lee, Hyunsuk Ko, Jongho Kim, Alan C. Bovik

It is well-known that natural images possess statistical regularities that can be captured by bandpass decomposition and divisive normalization processes that approximate early neural processing in the human visual system.

Frame Optical Flow Estimation

RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content

1 code implementation26 Jan 2021 Zhengzhong Tu, Xiangxu Yu, Yilin Wang, Neil Birkbeck, Balu Adsumilli, Alan C. Bovik

However, these models are either incapable or inefficient for predicting the quality of complex and diverse UGC videos in practical applications.

Video Quality Assessment

A Hitchhiker's Guide to Structural Similarity

1 code implementation16 Jan 2021 Abhinau K. Venkataramanan, Chengyang Wu, Alan C. Bovik, Ioannis Katsavounidis, Zafar Shahid

The Structural Similarity (SSIM) Index is a very widely used image/video quality model that continues to play an important role in the perceptual evaluation of compression algorithms, encoding recipes and numerous other image/video processing algorithms.


The VIP Gallery for Video Processing Education

no code implementations29 Dec 2020 Todd Goodall, Alan C. Bovik

Towards enhancing DVP education we have created a carefully constructed gallery of educational tools that is designed to complement a comprehensive corpus of online lectures by providing examples of DVP on real-world content, along with a user-friendly interface that organizes numerous key DVP topics ranging from analog video, to human visual processing, to modern video codecs, etc.

Learning Theory

ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction

1 code implementation26 Oct 2020 Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, Alan C. Bovik

We consider the problem of conducting frame rate dependent video quality assessment (VQA) on videos of diverse frame rates, including high frame rate (HFR) videos.

Frame Video Quality Assessment +2

Learning to Compress Videos without Computing Motion

1 code implementation29 Sep 2020 Meixu Chen, Todd Goodall, Anjul Patney, Alan C. Bovik

Our framework exploits the regularities inherent to video motion, which we capture by using displaced frame differences as video representations to train the neural network.

Frame Motion Estimation +3

Adaptive Debanding Filter

no code implementations22 Sep 2020 Zhengzhong Tu, Jessie Lin, Yilin Wang, Balu Adsumilli, Alan C. Bovik

Banding artifacts, which manifest as staircase-like color bands on pictures or video frames, is a common distortion caused by compression of low-textured smooth regions.


Subjective and Objective Quality Assessment of High Frame Rate Videos

1 code implementation22 Jul 2020 Pavan C. Madhusudana, Xiangxu Yu, Neil Birkbeck, Yilin Wang, Balu Adsumilli, Alan C. Bovik

We also conducted a holistic evaluation of existing state-of-the-art Full and No-Reference video quality algorithms, and statistically benchmarked their performance on the new database.


Perceptually Optimizing Deep Image Compression

no code implementations3 Jul 2020 Li-Heng Chen, Christos G. Bampis, Zhi Li, Andrey Norkin, Alan C. Bovik

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.

Image Compression

Capturing Video Frame Rate Variations via Entropic Differencing

no code implementations19 Jun 2020 Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, Alan C. Bovik

High frame rate videos are increasingly getting popular in recent years, driven by the strong requirements of the entertainment and streaming industries to provide high quality of experiences to consumers.

Frame Video Quality Assessment

UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content

5 code implementations29 May 2020 Zhengzhong Tu, Yilin Wang, Neil Birkbeck, Balu Adsumilli, Alan C. Bovik

Recent years have witnessed an explosion of user-generated content (UGC) videos shared and streamed over the Internet, thanks to the evolution of affordable and reliable consumer capture devices, and the tremendous popularity of social media platforms.

feature selection Video Quality Assessment +2

BBAND Index: A No-Reference Banding Artifact Predictor

no code implementations27 Feb 2020 Zhengzhong Tu, Jessie Lin, Yilin Wang, Balu Adsumilli, Alan C. Bovik

Banding artifact, or false contouring, is a common video compression impairment that tends to appear on large flat regions in encoded videos.

Frame Video Compression

ProxIQA: A Proxy Approach to Perceptual Optimization of Learned Image Compression

1 code implementation19 Oct 2019 Li-Heng Chen, Christos G. Bampis, Zhi Li, Andrey Norkin, Alan C. Bovik

By building on top of an existing deep image compression model, we are able to demonstrate a bitrate reduction of as much as $31\%$ over MSE optimization, given a specified perceptual quality (VMAF) level.

Image Compression

Speeding up VP9 Intra Encoder with Hierarchical Deep Learning Based Partition Prediction

1 code implementation15 Jun 2019 Somdyuti Paul, Andrey Norkin, Alan C. Bovik

In VP9 video codec, the sizes of blocks are decided during encoding by recursively partitioning 64$\times$64 superblocks using rate-distortion optimization (RDO).

Large-Scale Study of Perceptual Video Quality

no code implementations5 Mar 2018 Zeina Sinno, Alan C. Bovik

We demonstrate the value of the new resource, which we call the LIVE Video Quality Challenge Database (LIVE-VQC), by conducting a comparison of leading NR video quality predictors on it.

Video Quality Assessment

A Probabilistic Quality Representation Approach to Deep Blind Image Quality Prediction

1 code implementation28 Aug 2017 Hui Zeng, Lei Zhang, Alan C. Bovik

Recognizing this, we propose a new representation of perceptual image quality, called probabilistic quality representation (PQR), to describe the image subjective score distribution, whereby a more robust loss function can be employed to train a deep BIQA model.

Blind Image Quality Assessment

Learning to Predict Streaming Video QoE: Distortions, Rebuffering and Memory

1 code implementation2 Mar 2017 Christos G. Bampis, Alan C. Bovik

Mobile streaming video data accounts for a large and increasing percentage of wireless network traffic.


Perceptual Quality Prediction on Authentically Distorted Images Using a Bag of Features Approach

1 code implementation15 Sep 2016 Deepti Ghadiyaram, Alan C. Bovik

Current top-performing blind perceptual image quality prediction models are generally trained on legacy databases of human quality opinion scores on synthetically distorted images.

Massive Online Crowdsourced Study of Subjective and Objective Picture Quality

no code implementations9 Nov 2015 Deepti Ghadiyaram, Alan C. Bovik

Towards overcoming these limitations, we designed and created a new database that we call the LIVE In the Wild Image Quality Challenge Database, which contains widely diverse authentic image distortions on a large number of images captured using a representative variety of modern mobile devices.

Blind Image Quality Assessment Small Data Image Classification

Blind Prediction of Natural Video Quality

1 code implementation IEEE Transacations on Image Processing 2014 Michele A. Saad, Alan C. Bovik, Christophe Charrier

3) We show that the proposed NSS and motion coherency models are appropriate for quality assessment of videos, and we utilize them to design a blind VQA algorithm that correlates highly with human judgments of quality.

Video Quality Assessment Visual Question Answering +1

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