Publications by Sven Kreiss | EPFL Graph Search

Traffic perception from aerial images using butterfly fields

Alexandre Massoud Alahi, George Adaimi, Sven Kreiss

Drones are nowadays considered as a valuable solution to monitor urban traffic. Object detectors face numerous challenges when dealing with high-resolution aerial images captured by drones, due to variations in altitude, viewing angle, and weather conditio ...

Pergamon-Elsevier Science Ltd2023

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 Institute of Electrical and Electronics Engineers2022

Perceiving Humans: from Monocular 3D Localization to Social Distancing

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

Perceiving humans in the context of Intelligent Transportation Systems (ITS) often relies on multiple cameras or expensive LiDAR sensors. In this work, we present a new cost-effective vision-based method that perceives humans' locations in 3D and their bod ...

IEEE Institute of Electrical and Electronics Engineers2022

Deep visual Re-identification with confidence

Alexandre Massoud Alahi, George Adaimi, Sven Kreiss

Transportation systems often rely on understanding the flow of vehicles or pedestrian. Fromtraffic monitoring at the city scale, to commuters in train terminals, recent progress in sensingtechnology make it possible to use cameras to better understand the ...

2021

Keypoint Communities

Alexandre Massoud Alahi, Sven Kreiss, Duncan Zauss

2021

Human Trajectory Forecasting in Crowds: A Deep Learning Perspective

Alexandre Massoud Alahi, Parth Ashit Kothari, Sven Kreiss

Since the past few decades, human trajectory forecasting has been a field of active research owing to its numerous real-world applications: evacuation situation analysis, traffic operations, deployment of social robots in crowded environments, to name a fe ...

IEEE Institute of Electrical and Electronics Engineers2021

MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni, Taylor Ferdinand Mordan

Monocular and stereo visions are cost-effective solutions for 3D human localization in the context of self-driving cars or social robots. However, they are usually developed independently and have their respective strengths and limitations. We propose a no ...

IEEE2021

Joint Human Pose Estimation and Stereo 3D Localization

Alexandre Massoud Alahi, Wenlong Deng, Sven Kreiss, Lorenzo Bertoni

We present an end-to-end trainable Neural Network architecture for stereo imaging that jointly locates and estimates human body poses in 3D. Our method defines a 2D pose for each human in a stereo pair of images and uses a correlation layer with a composit ...

IEEE2020

Deep Visual Re-Identification with Confidence

Alexandre Massoud Alahi, George Adaimi, Sven Kreiss

Transportation systems often rely on understanding the flow of vehicles or pedestrian. From traffic monitoring at the city scale, to commuters in train terminals, recent progress in sensing technology make it possible to use cameras to better understand th ...

2019

MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

We tackle the fundamentally ill-posed problem of 3D human localization from monocular RGB images. Driven by the limitation of neural networks outputting point estimates, we address the ambiguity in the task by predicting confidence intervals through a loss ...

2019

PifPaf: Composite Fields for Human Pose Estimation

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

We propose a new bottom-up method for multi-person 2D human pose estimation that is particularly well suited for urban mobility such as self-driving cars and delivery robots. The new method, PifPaf, uses a Part Intensity Field (PIF) to localize body parts ...

IEEE2019

Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

Alexandre Massoud Alahi, Yuejiang Liu, Sven Kreiss, Changan Chen

Mobility in an effective and socially-compliant manner is an essential yet challenging task for robots operating in crowded spaces. Recent works have shown the power of deep reinforcement learning techniques to learn socially cooperative policies. However, ...

IEEE2019

Next Steps for Social Force with Big Data

Alexandre Massoud Alahi, Sven Kreiss

2019

Automatic Differentiation in Social Force Models

Alexandre Massoud Alahi, Sven Kreiss

2019