activity
20182022
most citedHybrid-MST: A Hybrid Active Sampling Strategy for Pairwise Preference Aggregation

22 citations · 72 across the 18 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

cs.GR2019★ 3 cited

Spectral domain decomposition method for physically-based rendering of photochromic/electrochromic glass windows

Guillaume Gbikpi-Benissan, Patrick Callet, Frederic Magoules

This paper covers the time consuming issues intrinsic to physically-based image rendering algorithms. First, glass materials optical properties were measured on samples of real gla…

cs.GR2019★ 3 cited

Spectral Domain Decomposition Method for Natural Lighting and Medieval Glass Rendering

Guillaume Gbikpi-Benissan, Remi Cerise, Patrick Callet +1

In this paper, we use an original ray-tracing domain decomposition method to address image rendering of naturally lighted scenes. This new method allows to particularly analyze ren…

cs.GR2019

Spectral domain decomposition method for physically-based rendering of Royaumont abbey

Guillaume Gbikpi-Benissan, Patrick Callet, Frederic Magoules

In the context of a virtual reconstitution of the destroyed Royaumont abbey church, this paper investigates computer sciences issues intrinsic to the physically-based image renderi…

cs.LG2019★ 1 cited

A New Ensemble Adversarial Attack Powered by Long-term Gradient Memories

Zhaohui Che, Ali Borji, Guangtao Zhai +3

Deep neural networks are vulnerable to adversarial attacks.

cs.MM2019★ 2 cited

Binocular Rivalry Oriented Predictive Auto-Encoding Network for Blind Stereoscopic Image Quality Measurement

Jiahua Xu, Wei Zhou, Zhibo Chen +2

Stereoscopic image quality measurement (SIQM) has become increasingly important for guiding stereo image processing and commutation systems due to the widespread usage of 3D conten…

cs.CV2019★ 6 cited

Adversarial Attacks against Deep Saliency Models

Zhaohui Che, Ali Borji, Guangtao Zhai +3

Currently, a plethora of saliency models based on deep neural networks have led great breakthroughs in many complex high-level vision tasks (e.g. scene description, object detectio…