RESEARCH PAPER / IEEE CSCN / Mar 2023
This paper presents the architectural considerations of integrating the non-IP-based service routing solution, Name-Based Routing, to the 5G user plane. While entirely preserving the control plane procedures on the terminal, the carefully crafted considerations herein argue for a new Session Management Function functionality and the transitioning of the N4 interface...
RESEARCH PAPER / IEEE Globecom Conference / Dec 2022
A reconfigurable intelligent surface (RIS) can be used to control the propagation of electromagnetic waves (EM). By deploying the RIS units in radio environment allows to steer the transmitted EM waves to areas that are otherwise shadowed by buildings or other geographic formations resulting in coverage enhancement. The gain offered...
RESEARCH PAPER / IEEE Communications Standards Magazine Special Issue on "5G Advanced" / Dec 2022
3GPP provided the specifications of 5G in Release 15. Releases 16 and 17 provided improvements to the system performance and supported the integration of new scenarios for verticals. The upcoming Release 18 will define “5G Advanced,” a milestone towards 6G. Artificial Intelligence (AI) and Machine Learning (ML) will be new...
RESEARCH PAPER / Elsevier Book : "Immersive Video Technologies" / Dec 2022
Get a broad overview of the different modalities of immersive video technologies—from omnidirectional video to light fields and volumetric video—from a multimedia processing perspective. From capture to representation, coding, and display, video technologies have been evolving significantly and in many different directions over the last few decades, with the ultimate...
RESEARCH PAPER / 2022 IEEE International Conference on Visual Communications and Image Processing / Dec 2022
Spatial frequency analysis and tranforms have served a central role in most engineered image and video lossy codecs. However, they do not seem appealing to Neural-Network (NN)-based image compression approaches. In this paper, we propose an end-to-end learned image compression method that exploits forward wavelet ransform to decompose the spatial...
RESEARCH PAPER / Picture Coding Symposium (PCS 2022) / Dec 2022
End-to-end trainable models are about to exceed the performance of the traditional handcrafted compression techniques on videos and images. The core idea is to learn a non- linear transformation into latent space, jointly with an entropy model of the latent distribution. These methods enforce the latent to follow some prior...
RESEARCH PAPER / IEEE Globecom 2022 / Dec 2022
Federated learning (FL) is a collaborative machine learning framework to enable different clients such as Internet of Things (IoT) devices to participate in a machine learning model training process, while preserving data privacy. Client selection is critical to determine the performance of FL. Most of the existing client selection methods...
RESEARCH PAPER / PCS 2022 (Picture Coding Symposium) / Dec 2022
End-to-end trainable models have reached the performance of traditional handcrafted compression techniques on videos and images. Since the parameters of these models are learned over large training sets, they are not optimal for any given image to be compressed. In this paper, we propose an instance-based fine-tuning of a subset...
RESEARCH PAPER / IEEE Globecom 2022 / Dec 2022
We present the Quantum Polar Decoder (QPD), a Quantum Annealing (QA) based decoder design for Polar error correction codes, which are becoming widespread in today’s 5G and tomorrow’s 6G networks. QPD’s design efficiently transforms a Polar code’s binary tree structured encoder into a quadratic polynomial form of compact length, making...
RESEARCH PAPER / ACM Multimedia Asia / Nov 2022
Innovation in video systems becomes cardinal in today's times when applications like video streaming and cloud gaming are at their peak and rising. This paper presents a new Gstreamer plugin (GSTH266enc) for Versatile Video Coding (VVC) encoder. VVC is the most recent international video coding standard that was finalized in...
RESEARCH PAPER / MILCOM 2022 / Nov 2022
The continued demand for spectrum has pressured governments to make more spectrum available to the commercial sector. This in turn has put pressure on government users of the spectrum to be more efficient even as their own demand for data grows. As a result, the US government is considering using...
RESEARCH PAPER / Workshop at NIPS 2022 - Memory in Artificial and Real Intelligence / Nov 2022
The Predicting Media Memorability task in the MediaEval evaluation campaign has1 been running annually since 2018 and several different tasks and data sets have been2 used over those years. This has allowed us to compare the performance of many3 techniques on the same data and in a reproducible way and...
RESEARCH PAPER / Web3D / Nov 2022
With new use cases in markets such as gaming, IoT, PC, and extended reality (AR/VR/MR), there is an increasing demand for richer haptic experiences. High-definition (HD) haptics, with effects ranging from subtle to sharp, textured effects that simulate different surfaces and sensations, and increasingly efficient vibration motors, are becoming the...
RESEARCH PAPER / IEEE Access / Oct 2022
Radio access network (RAN) technologies continue to witness an insatiable rate of development progress, with Open-RAN gaining the most recent momentum. In the O-RAN structure, the RAN intelligent controller (RIC) provides a host for various AI/ML models. This article introduces principles of machine learning (ML), in particular, reinforcement learning (RL)...
RESEARCH PAPER / MOBICOM 22 - Winter / Oct 2022
With the continuous growth of the Internet of Things (IoT),the trend of increasing connection to the Internet of billionsof new IoT devices will continue. To increase network capa-bility to support a large number of active devices accessing anetwork (i.e.,massive IoT connectivity), this work presentsIoT-ResQ, a warm-started quantum annealing-based multi-device detector...
RESEARCH PAPER / IEEE International Conference in Image Processing / Oct 2022
Generative adversarial networks (GANs) have proven to be surprisingly efficient for image editing by inverting and manipulating the latent code corresponding to an input real image. This editing property emerges from the disentangled nature of the latent space. In this paper, we identify that the facial attribute disentanglement is not...
RESEARCH PAPER / European Conference on Computer Vision / Oct 2022
We present a new encoder architecture for GAN inversion. The task is to reconstruct a real image from the latent space of a pre-trained Generative Adversarial Network (GAN). Unlike previous encoder-based methods which predict only a latent code from a real image, the proposed encoder maps the given image to...
RESEARCH PAPER / Breizh Video Tech / Oct 2022
The increasing popularity of virtual, augmented, and mixed reality (VR/AR/MR) applications is driving the media industry to explore the creation and delivery of new immersive experiences. A volumetric video consists of a sequence of frames, where each frame is a static three-dimensional (3D) representation of a real-world object or scene...
RESEARCH PAPER / ACM Multimedia 2022 Workshop / Oct 2022
We propose in this paper a new paradigm for facial video compression. We leverage the generative capacity of GANs such as StyleGAN to represent and compress a video, including intra and inter compression. Each frame is inverted in the latent space of StyleGAN, from which the optimal compression is learned....
RESEARCH PAPER / ACM Multimedia 2022 Workshop / Oct 2022
Point cloud compression (PCC) serves as a crucial phase in various 3-D applications, owing to the universality of the point cloud format. Ideally, 3D point clouds endeavor to depict object/scene surfaces that are continuous. Practically, as a set of discrete samples, point clouds are locally disconnected and sparsely distributed. This...
