Hybrid Spatial and Temporal Error Concealment for Distributed Video Coding

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Video DeepFakes are fake media created with Deep Learning (DL) that manipulate a person’s expression or identity. Most current DeepFake detection methods analyze each frame independently, ignoring inconsistencies and unnatural movements between frames. Som ...

The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual arti ...

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

Visual data play a crucial role in modern society, and the rate at which images and videos are acquired, stored, and exchanged every day is rapidly increasing. Image compression is the key technology that enables storing and sharing of visual content in an ...

In 1948, Claude Shannon laid the foundations of information theory, which grew out of a study to find the ultimate limits of source compression, and of reliable communication. Since then, information theory has proved itself not only as a quest to find the ...

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

Forecasting pedestrians' future motions is essential for autonomous driving systems to safely navigate in urban areas. However, existing prediction algorithms often overly rely on past observed trajectories and tend to fail around abrupt dynamic changes, s ...

With the emergence of social networks and improvements in the internet speed, the video data has become an ever-increasing portion of the global internet traffic. Besides the content, the quality of a video sequence is an important issue at the user end wh ...

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

Thanks to its capability of acquiring full-view frames at multiple kilohertz, ultrafast ultrasound imaging unlocked the analysis of rapidly changing physical phenomena in the human body, with pioneering applications such as ultrasensitive flow imaging in t ...

Lossy image compression is a popular, simple and effective solution to reduce the amount of data representing digital pictures. In most lossy compression methods, the reduced volume of data in bits is achieved at the expense of introducing visual artifacts ...

Nowadays, image and video are the data types that consume most of the resources of modern communication channels, both in fixed and wireless networks. Thus, it is vital to compress visual data as much as possible, while maintaining some target quality leve ...

Point cloud is a promising imaging modality for the representation of 3D media. The vast volume of data associated with it requires efficient compression solutions, with lossy algorithms leading to larger bit-rate savings at the expense of visual impairmen ...

Human motion prediction, the task of predicting future 3D human poses given a sequence of observed ones, has been mostly treated as a deterministic problem. However, human motion is a stochastic process: Given an observed sequence of poses, multiple future ...

This paper presents a quality evaluation study of point cloud codecs that have been recently standardised by the MPEG committee. In particular, a subjective experiment to assess their performance in terms of bitrate against visual quality is designed and r ...

Human motion prediction is a necessary component for many applications in robotics and autonomous driving. Recent methods propose using sequence-to-sequence deep learning models to tackle this problem. However, they do not focus on exploiting different tem ...

In my thesis, I reveal several already-existing and emerging challenges in multi-objective management of multiprocessor systems, and address them through novel solutions, from heuristics to RL, depending on the complexity of the problem. Conventional multi ...

In the field of UAV object tracking, correlation filter based approaches have received lots of attention due to their computational efficiency. The methods learn filters by the ridge regression and generate response maps to distinguish the specified target ...

The rapid development of digital imaging and video has placed visual contents in the heart of our lives. Digital multimedia span a vast number of areas from business to leisure, including but not limited to education, medicine, accessibility, training, adv ...

Hybrid Spatial and Temporal Error Concealment for Distributed Video Coding

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Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Automated Human Motion Analysis and Synthesis

JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion

Feature-based no-reference video quality assessment using Extra Trees

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking

Performance Evaluation of Objective Image Quality Metrics on Conventional and Learning-Based Compression Artifacts

Learning-based Image Coding: Early Solutions Reviewing and Subjective Quality Evaluation

Benchmarking of objective quality metrics for point cloud compression

A Stochastic Conditioning Scheme for Diverse Human Motion Prediction

Quality Evaluation Of Static Point Clouds Encoded Using MPEG Codecs

Motion Prediction Using Temporal Inception Module

Multi-Objective Management of Multiprocessor Systems: From Heuristics to Reinforcement Learning

Learning Temporary Block-Based Bidirectional Incongruity-Aware Correlation Filters for Efficient UAV Object Tracking

Image Compression and Quality Assessment using Convolutional Neural Networks