no code implementations • 4 May 2022 • Saeed Ranjbar Alvar, Mateen Ulhaq, Hyomin Choi, Ivan V. Bajić
In this paper, we present a learning-based image compression framework where image denoising and compression are performed jointly.
no code implementations • 3 May 2022 • Saeed Ranjbar Alvar, Korcan Uyanik, Ivan V. Bajić
Traffic scene analysis is important for emerging technologies such as smart traffic management and autonomous vehicles.
no code implementations • 10 Mar 2022 • Saeed Ranjbar Alvar, Lanjun Wang, Jian Pei, Yong Zhang
Image-to-image translation models are shown to be vulnerable to the Membership Inference Attack (MIA), in which the adversary's goal is to identify whether a sample is used to train the model or not.
no code implementations • 30 Jan 2022 • Saeed Ranjbar Alvar, Ivan V. Bajić
This document describes a noise generator that simulates realistic noise found in smartphone cameras.
no code implementations • 25 Sep 2020 • Saeed Ranjbar Alvar, Ivan V. Bajić
Moreover, we provide analytical characterization of the full Pareto set for 2-stream k-task systems, and bounds on the Pareto set for 3-stream 2-task systems.
no code implementations • 14 Feb 2020 • Saeed Ranjbar Alvar, Ivan V. Bajić
In CI, a deep neural network is split between the mobile device and the cloud.
no code implementations • 7 Feb 2019 • Jianglin Fu, Saeed Ranjbar Alvar, Ivan V. Bajic, Rodney G. Vaughan
360-degree cameras offer the possibility to cover a large area, for example an entire room, without using multiple distributed vision sensors.
no code implementations • 30 Apr 2018 • Saeed Ranjbar Alvar, Ivan V. Bajić
Object tracking is the cornerstone of many visual analytics systems.
no code implementations • 30 Oct 2017 • Saeed Ranjbar Alvar, Hyomin Choi, Ivan V. Bajic
Finding faces in images is one of the most important tasks in computer vision, with applications in biometrics, surveillance, human-computer interaction, and other areas.
no code implementations • 9 Sep 2017 • Saeed Ranjbar Alvar, Hyomin Choi, Ivan V. Bajic
We focus on one of the poster problems of visual analytics -- face detection -- and approach the issue of reducing the computation by asking: Is it possible to detect a face without full image reconstruction from the High Efficiency Video Coding (HEVC) bitstream?