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

Mathieu Salzmann, Zheng Dang, Jiancheng Yang, Haobo Jiang

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

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

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

Pavlos Nikolopoulos, Muhammad Abdullah, Aikaterini Argyraki, 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, Van Nguyen Nguyen, Yang Xiao

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, Nikolaos Dimitriadis, Ahmet Caner Yüzügüler

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, Solal Vincenzo Pirelli, Aikaterini Argyraki

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, Pascal Felber

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

Eric Bezzam, Robin Scheibler

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