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Related publications (24)

Center-Based Decoupled Point Cloud Registration for 6D Object Pose Estimation

Mathieu Salzmann, Jiancheng Yang, Zheng Dang

In this paper, we propose a novel center-based decoupled point cloud registration framework for robust 6D object pose estimation in real-world scenarios. Our method decouples the translation from the entire transformation by predicting the object center an ...

Ieee Computer Soc2023

Understanding Revision Behavior in Adaptive Writing Support Systems for Education

Tanja Christina Käser Jacober, Paola Mejia Domenzain, Thiemo Wambsganss, Luca Mouchel

Revision behavior in adaptive writing support systems is an important and relatively new area of research that can improve the design and effectiveness of these tools, and promote students' self-regulated learning (SRL). Understanding how these tools are u ...

Zenodo2023

Localizing Traffic Differentiation

Aikaterini Argyraki, Pavlos Nikolopoulos, Muhammad Abdullah, Zeinab Shmeis

Network neutrality is important for users, content providers, policymakers, and regulators interested in understanding how network providers differentiate performance. When determining whether a network differentiates against certain traffic, it is importa ...

2023

Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions

Mathieu Salzmann, Vincent Lepetit, Yinlin Hu

We present a method that can recognize new objects and estimate their 3D pose in RGB images even under partial occlusions. Our method requires neither a training phase on these objects nor real images depicting them, only their CAD models. It relies on a s ...

IEEE COMPUTER SOC2022

U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search

Pascal Frossard, Ahmet Caner Yüzügüler, Nikolaos Dimitriadis

Optimizing resource utilization in target platforms is key to achieving high performance during DNN inference. While optimizations have been proposed for inference latency, memory footprint, and energy consumption, prior hardware-aware neural architecture ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

On the Scalability of Vision-based Drone Swarms in the Presence of Occlusions

Dario Floreano, Fabian Maximilian Schilling, Enrica Soria

Vision-based drone swarms have recently emerged as a promising alternative to address the fault-tolerance and flexibility limitations of centralized and communication-based aerial collective systems. Although most vision-based control algorithms rely on th ...

2022

Automated Verification of Network Function Binaries

George Candea, Aikaterini Argyraki, Solal Vincenzo Pirelli

Formally verifying the correctness of software network functions (NFs) is necessary for network reliability, yet existing techniques require full source code and mandate the use of specific data structures. We describe an automated technique to verify NF b ...

USENIX Association2022

NVCache: A Plug-and-Play NVMM-based I/O Booster for Legacy Systems

Rafael Pereira Pires

This paper introduces NVCache, an approach that uses a non-volatile main memory (NVMM) as a write cache to improve the write performance of legacy applications. We compare NVCache against file systems tailored for NVMM (Ext4-DAX and NOVA) and with I/O-heav ...

IEEE2021

Pedestrian intention prediction: A convolutional bottom-up multi-task approach

Alexandre Massoud Alahi, Taylor Ferdinand Mordan

The ability to predict pedestrian behaviour is crucial for road safety, traffic management systems, Advanced Driver Assistance Systems (ADAS), and more broadly autonomous vehicles. We present a vision-based system that simultaneously locates where pedestri ...

2021

A Study on More Realistic Room Simulation for Far-Field Keyword Spotting

Robin Scheibler, Eric Bezzam

We investigate the impact of more realistic room simulation for training far-field keyword spotting systems without fine-tuning on in-domain data. To this end, we study the impact of incorporating the following factors in the room impulse response (RIR) ge ...

IEEE2020

Safe Initialization of Objects

Martin Odersky, Fengyun Liu, Paolo Giosuè Giarrusso, Angelos Bimpoudis

Every newly created object goes through several initialization states: starting from a state where all fields are uninitialized until all of them are assigned. Any operation on the object during its initialization process, which usually happens in the cons ...

2020

A Type-and-Effect System for Object Initialization

Martin Odersky, Fengyun Liu, Paolo Giosuè Giarrusso, Angelos Bimpoudis

ASSOC COMPUTING MACHINERY2020

Using an antenna as a tool for studying microturbulence and zonal structures in tokamaks with a global gyrokinetic GPU-enabled particle-in-cell code

Noé Thomas Elie Ohana

In order to get a better understanding of the interaction of plasma microinstabilities and associated turbulence with specific modes, an antenna is implemented in the global gyrokinetic Particle-In-Cell (PIC) code ORB5. It consists in applying an external ...

EPFL2020

Safe initialization of objects

Fengyun Liu

The inception of object-oriented programming introduces a category of bugs related to object construction: initialization errors. Every newly created object goes through several initialization states: starting from a state where all fields are uninitialize ...

EPFL2020

Gyrokinetic simulations on many- and multi-core architectures with the global electromagnetic Particle-In-Cell Code ORB5

Laurent Villard, Stephan Brunner, Emmanuel Lanti, Noé Thomas Elie Ohana, Claudio Gheller

Gyrokinetic codes in plasma physics need outstanding computational resources to solve increasingly complex problems, requiring the effective exploitation of cutting-edge HPC architectures. This paper focuses on the enabling of ORB5, a state-of-the-art, fir ...

2021

The Sixth Visual Object Tracking VOT2018 Challenge Results

Wei Wu, Qiang Wang, Bo Li, Yunpeng Li, Feng Li, Erhan Gündogdu

The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

PyLandStats: An open-source Pythonic library to compute landscape metrics

Martí Bosch Padrós

Quantifying the spatial pattern of landscapes has become a common task of many studies in landscape ecology. Most of the existing software to compute landscape metrics is not well suited to be used in interactive environments such as Jupyter notebooks nor ...

2019

Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images

Matthieu Jean-Michel Philippe Broisin

Identifying nuclei is often a critical first step in analyzing microscopy images of cells and classical image processing algorithms are most commonly used for this task. Recent developments in deep learning can yield superior accuracy, but typical evaluati ...

2019

Heterogeneous Face Recognition Using Domain Specific Units

Sébastien Marcel, André Anjos, Tiago De Freitas Pereira

The task of Heterogeneous Face Recognition consists in matching face images that are sensed in different domains, such as sketches to photographs (visual spectra images), thermal images to photographs or near-infrared images to photographs. In this work we ...

2019

Hardware Acceleration of HDR-Image Tone Mapping on an FPGA-CPU Platform Through High-Level Synthesis

Christian Enz, Vincent Frédéric Camus, Alessandro Pezzotta, Jérémy Lucien Maurice Schlachter, Mattia Cacciotti

In this paper, the hardware acceleration of a tone-mapping algorithm for High-Dynamic-Range image processing is presented. Starting from the C++ source code, High-Level Synthesis has been performed using Xilinx SDSoC for a Xilinx Zynq SoC device. After an ...

IEEE2018