paper-with-me

Papers

FovVideoVDP: A visible difference predictor for wide field-of-view video

2021-04-01 · ACM Transactions on Graphics 2021 4 · Rafał K. Mantiuk, Gyorgy Denes, ALEXANDRE CHAPIRO, Anton Kaplanyan, GIZEM RUFO, ROMAIN BACHY, Trisha Lian, Anjul Patney

FovVideoVDP is a video difference metric that models the spatial, temporal, and peripheral aspects of perception. While many other metrics are available, our work provides the first practical treatment of these three central aspects of vision simultaneously. The complex interplay between spatial and temporal sensitivity across retinal locations is especially important for displays that cover a large field-of-view, such as Virtual and Augmented Reality displays, and associated methods, such as foveated rendering. Our metric is derived from psychophysical studies of the early visual system, which model spatio-temporal contrast sensitivity, cortical magnification and contrast masking. It accounts for physical specification of the display (luminance, size, resolution) and viewing distance. To validate the metric, we collected a novel foveated rendering dataset which captures quality degradation due to sampling and reconstruction. To demonstrate our algorithm’s generality, we test it on 3 independent foveated video datasets, and on a large image quality dataset, achieving the best performance across all datasets when compared to the state-of-the-art.

📄 PDF Abstract BibTeX

Code (1)

gfxdisp/FovVideoVDP pytorch

Tasks

Sensitivity

Similar Papers 제목 키워드 기반

Visual Interaction Networks

2017-06-05 · Nicholas Watters, Andrea Tacchetti, Theophane Weber, Razvan Pascanu 외

From just a glance, humans can make rich predictions about the future state of a wide range of physical systems. On the other hand, modern approaches from engineering, robotics, and graphics are often restricted to narro…

Decision Making

Visual Interaction Networks: Learning a Physics Simulator from Video

2017-12-01 · NeurIPS 2017 12 · Nicholas Watters, Daniel Zoran, Theophane Weber, Peter Battaglia 외

From just a glance, humans can make rich predictions about the future of a wide range of physical systems. On the other hand, modern approaches from engineering, robotics, and graphics are often restricted to narrow dom…

Decision Making

CameraVDP: Perceptual Display Assessment with Uncertainty Estimation via Camera and Visual Difference Prediction

2025-09-10 · Yancheng Cai, Robert Wanat, Rafal Mantiuk arxiv

Accurate measurement of images produced by electronic displays is critical for the evaluation of both traditional and computational displays. Traditional display measurement methods based on sparse radiometric sampling a…

Occluded Pedestrian Detection with Visible IoU and Box Sign Predictor

2019-11-26 · Ruiqi Lu, Huimin Ma

Training a robust classifier and an accurate box regressor are difficult for occluded pedestrian detection. Traditionally adopted Intersection over Union (IoU) measurement does not consider the occluded region of the obj…

Pedestrian Detection

Distributed Online Linear Regression

2019-02-13 · Deming Yuan, Alexandre Proutiere, Guodong Shi

We study online linear regression problems in a distributed setting, where the data is spread over a network. In each round, each network node proposes a linear predictor, with the objective of fitting the \emph{network-…

regression