Publication

PifPaf: Composite Fields for Human Pose Estimation

Publications associées (39)

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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 ...

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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 ...

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Chaotic microcomb inertia-free parallel ranging

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Ever growing pixel acquisition rates in the fields of augmented reality, autonomous driving and robotics have increased interest in solid state beam scanning without moving parts. Modern photonic integrated laser ranging advances towards passive beam steer ...

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Encoder-Decoder Models for Human Segmentation and Motion Analysis

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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 ...

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Reshaping Perception for Autonomous Driving with Semantic Keypoints

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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, ...

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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

Vehicle trajectory prediction works, but not everywhere

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

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. ...

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OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

Many image-based perception tasks can be formulated as detecting, associating and tracking semantic keypoints, e.g., human body pose estimation and tracking. In this work, we present a general framework that jointly detects and forms spatio-temporal keypoi ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

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

Yujie He, Yue Pan

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

Stochastic Optimal Control for Autonomous Driving Applications via Polynomial Chaos Expansions

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Model-based methods in autonomous driving and advanced driving assistance gain importance in research and development due to their potential to contribute to higher road safety. Parameters of vehicle models, however, are hard to identify precisely or they ...

2021

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