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Behavioral priors for detection and tracking of pedestrians in video sequences

Related publications (38)

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Attribute Prediction as Multiple Instance Learning

Devis Tuia, Diego Marcos Gonzalez

Attribute-based representations help machine learning models perform tasks based on human understandable concepts, allowing a closer human-machine collaboration. However, learning attributes that accurately reflect the content of an image is not always str ...

2022

Human-Centered Scene Understanding via Crowd Counting

Weizhe Liu

Human-centered scene understanding is the process of perceiving and analysing a dynamic scene observed through a network of sensors with emphasis on human-related activities. It includes the visual perception of human-related activities from either single ...

EPFL2021

"Venice Art Center" - Un nouveau centre d'art sur le Canal Grande

Tancredi Kusch

Venise et son architecture appartiennent à une réalité suspendue entre les époques. Si l’on fait abstraction du nombre alarmant de touristes, lorsqu’on explore les ruelles labyrinthiques, lorsqu’on admire d’un vaporetto les palais qui s’affichent sur le Ca ...

2020

Real-time camera pose estimation for sports fields

Pascal Fua, Charles Dubout, Horesh Beny Ben Shitrit, Pablo Marquez Neila, Leonardo Citraro, Stefano Savarè

Given an image sequence featuring a portion of a sports field filmed by a moving and uncalibrated camera, such as the one of the smartphones, our goal is to compute automatically in real time the focal length and extrinsic camera parameters for each image ...

2020

Image reconstruction method based on a trained non-linear mapping

Jean-Philippe Thiran, Dimitris Perdios, Marcel Arditi, Adrien Besson, Florian Martinez

The present invention concerns an array processing image reconstruction method comprising: receiving (13) a set of echo waveforms as measurements from the object of interest; defining (15) a measurement model linking an unknown image of the object to the m ...

2020

Dual Generator Generative Adversarial Networks for Multi-domain Image-to-Image Translation

Yan Yan, Wei Wang

State-of-the-art methods for image-to-image translation with Generative Adversarial Networks (GANs) can learn a mapping from one domain to another domain using unpaired image data. However, these methods require the training of one specific model for every ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Learn to synthesize and synthesize to learn

Jean-Philippe Thiran, Hazim Kemal Ekenel, Mohammad Saeed Rad

Attribute guided face image synthesis aims to manipulate attributes on a face image. Most existing methods for image-to-image translation can either perform a fixed translation between any two image domains using a single attribute or require training data ...

2019

Learn to synthesize and synthesize to learn

Jean-Philippe Thiran, Hazim Kemal Ekenel, Mohammad Saeed Rad

ACADEMIC PRESS INC ELSEVIER SCIENCE2019

Learning to Find Unpaired Cross-Spectral Correspondences

Seungryong Kim

We present a deep architecture and learning framework for establishing correspondences across cross-spectral visible and infrared images in an unpaired setting. To overcome the unpaired cross-spectral data problem, we design the unified image translation a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Learning to See through Reflections

Sabine Süsstrunk

"Pictures of objects behind a glass are difficult to interpret" "and understand due to the superposition of two real images: a reflection layer and a background layer. Separation of these two layers is challenging due to the ambiguities in as- signing text ...

IEEE2018