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20202024
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cs.CV2024

OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras

Muhammad Rameez Ur Rahman, Jhony H. Giraldo, Indro Spinelli +2

Event cameras, known for low-latency operation and superior performance in challenging lighting conditions, are suitable for sensitive computer vision tasks such as semantic segmen…

cs.CV2024

Privacy-Preserving Adaptive Re-Identification without Image Transfer

Hamza Rami, Jhony H. Giraldo, Nicolas Winckler +1

Re-Identification systems (Re-ID) are crucial for public safety but face the challenge of having to adapt to environments that differ from their training distribution. Furthermore,…

cs.CV2024

Source-Guided Similarity Preservation for Online Person Re-Identification

Hamza Rami, Jhony H. Giraldo, Nicolas Winckler +1

Online Unsupervised Domain Adaptation (OUDA) for person Re-Identification (Re-ID) is the task of continuously adapting a model trained on a well-annotated source domain dataset to…

cs.CV2023

Predictive Coding For Animation-Based Video Compression

Goluck Konuko, Stéphane Lathuilière, Giuseppe Valenzise

We address the problem of efficiently compressing video for conferencing-type applications. We build on recent approaches based on image animation, which can achieve good reconstru…

cs.CV2022

Online Unsupervised Domain Adaptation for Person Re-identification

Hamza Rami, Matthieu Ospici, Stéphane Lathuilière

Unsupervised domain adaptation for person re-identification (Person Re-ID) is the task of transferring the learned knowledge on the labeled source domain to the unlabeled target do…

cs.CV2020

Ultra-low bitrate video conferencing using deep image animation

Goluck Konuko, Giuseppe Valenzise, Stéphane Lathuilière

In this work we propose a novel deep learning approach for ultra-low bitrate video compression for video conferencing applications. To address the shortcomings of current video com…