Publications associées à Chaotic microcomb inertia-free parallel ranging

Publications associées (35)

Programming Light Propagation for Efficient Artificial Intelligence

Contemporary artificial intelligence (AI) models' exponentially growing complexity translates to their expanding skill sets. They can create language or image content mimicking human creativity and understanding, becoming indispensable tools in education, ...

EPFL2025

Optical Processors for AI Computing and Networking

Mustafa Yildirim

Computing has long been central to technological advancements, where each leap in compute power has catalyzed applications once thought impossible, such as smartphones. Recently, the exponential growth in the compute demand of artificial intelligence (AI) ...

EPFL2025

TTool: A Supervised Artificial Intelligence-Assisted Visual Pose Detector for Tool Heads in Augmented Reality Woodworking

Naravich Chutisilp, Yves Weinand, Julien Gamerro, Andrea Settimi, Florian Aymanns

We present TimberTool (TTool v2.1.1), a software designed for woodworking tasks assisted by augmented reality (AR), emphasizing its essential function of the real-time localization of a tool head’s poses within camera frames. The localization process, a fu ...

2024

Exploring van der Waals materials with high anisotropy: geometrical and optical approaches

Arslan Mazitov

The emergence of van der Waals (vdW) materials resulted in the discovery of their high optical, mechanical, and electronic anisotropic properties, immediately enabling countless novel phenomena and applications. Such success inspired an intensive search fo ...

2024

Reshaping Perception for Autonomous Driving with Semantic Keypoints

Lorenzo Bertoni

The field of artificial intelligence is set to fuel the future of mobility by driving forward the transition from advanced driver-assist systems to fully autonomous vehicles (AV). Yet the current technology, backed by cutting-edge deep learning techniques, ...

EPFL2022

Encoder-Decoder Models for Human Segmentation and Motion Analysis

Isinsu Katircioglu

Detecting people from 2D images and analyzing their motion in 3D have been long standing computer vision problems central to numerous applications such as autonomous driving and athletic training. Recently, with the availability of large amounts of trainin ...

EPFL2022

Pedestrian 3D Bounding Box Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yi Zhou Ju

Safety is still the main issue of autonomous driving, and in order to be globally deployed, they need to predict pedestrians' motions sufficiently in advance. While there is a lot of research on coarse-grained (human center prediction) and fine-grained pre ...

2022

Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion

Alexandre Massoud Alahi, Taylor Ferdinand Mordan

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 ...

2022

Optimizing Data Processing for Nanodiamond Based Relaxometry

Mayeul Sylvain Chipaux

The nitrogen-vacancy (NV) center in diamond is a powerful and versatile quantum sensor for diverse quantities. In particular, relaxometry (or T1), can be used to detect magnetic noise at the nanoscale. For experiments with single NV centers the analysis of ...

WILEY2023

Long Term Motion Prediction Using Keyposes

Pascal Fua, Mathieu Salzmann, Wei Wang, Sena Kiciroglu

Long term human motion prediction is essential in safety-critical applications such as human-robot interaction and autonomous driving. In this paper we show that to achieve long term forecasting, predicting human pose at every time instant is unnecessary. ...

IEEE2022

Vehicle trajectory prediction works, but not everywhere

Alexandre Massoud Alahi, Seyed Mohsen Moosavi Dezfooli, Saeed Saadatnejad, Mohammadhossein Bahari, Ahmad Rahimi

Vehicle trajectory prediction is nowadays a fundamental pillar of self-driving cars. Both the industry and research communities have acknowledged the need for such a pillar by providing public benchmarks. While state-of-the-art methods are impressive, i.e. ...

IEEE2022

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Saeed Saadatnejad

Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...

EPFL2023

Visualization, Interactive Handling and Simulation of Molecules in Commodity Augmented Reality in Web Browsers Using moleculARweb's Virtual Modeling Kits

Matteo Dal Peraro, Luciano Andres Abriata, Lucien Fabrice Krapp, Fabio Jose Cortes Rodriguez

moleculARweb (https://molecularweb.epfl.ch) began as a website for education and outreach in chemistry and structural biology through augmented reality (AR) content that runs in the web browsers of regular devices like smartphones, tablets, and computers. ...

SWISS CHEMICAL SOC2022

Detecting Anomalies and Obstacles in Road Scenes

Krzysztof Maciej Lis

We address the problem of segmenting anomalies and unusual obstacles in road scenes for the purpose of self-driving safety. The objects in question are not present in the common training sets as it is not feasible to collect and annotate examples for every ...

EPFL2023

Haptics based collaborative steering control in automated driving environments

Tomohiro Nakade

A vehicle's steering is a particular system in that it is exposed to individual subjective reviews based on criteria that are hard to assess quantitatively. Haptic design of such systems is a prime concern that has been at the center of industrial developm ...

EPFL2023

Haptics based multi-level collaborative steering control for automated driving

Hannes Bleuler, Jürg Alexander Schiffmann, Robert Fuchs, Tomohiro Nakade

Increasing the capability of automated driving vehicles is motivated by environmental, productivity, and traffic safety benefits. But over-reliance on the automation system is known to cause accidents. The role of the driver cannot be underestimated as it ...

2023

Cockroach: an open-source tool for point cloud processing in cad

Yves Weinand, Julien Gamerro, Andrea Settimi, Petras Vestartas

In the architecture, engineering and construction (AEC) sector, the use of point cloud data is not a novelty. Usually employed to retrieve data for inspecting construction sites or retrofitting pre-existing buildings, sensors like LiDAR cameras have been k ...

Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)2022

Analysis of Non-Canonical Body-Conformal Arrays with Polarization Decomposition

Anja Skrivervik, Denys Nikolayev

Conformal phased arrays can be found in many applications due to their ability to fit tridimensional surfaces and, thanks to their scanning performance, can excel planar arrays. However, most of the previously proposed analysis methods can be applied only ...

IEEE2023

MULLS: Versatile LiDAR SLAM via Multi-metric Linear Least Square

Yujie He

The rapid development of autonomous driving and mobile mapping calls for off-the-shelf LiDAR SLAM solutions that are adaptive to LiDARs of different specifications on various complex scenarios. To this end, we propose MULLS, an efficient, low-drift, and ve ...

IEEE2021

GeSn as next-generation material for short-wave infrared single-photon detection

Andrea Giunto

In recent years, the automotive industry has aspired to bring self-driving vehicles to the general public and light detection and ranging (LiDAR) sensors have emerged as the preferred solution for car vision systems. At present, LiDAR technologies employ e ...

EPFL2023