Publications associées à Learning Real-Time Perspective Patch Rectification

Publications associées (27)

Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes

Tanja Christina Käser Jacober, Antoine Bosselut, Thiemo Wambsganss, Seyed Parsa Neshaei, Jibril Albachir Frej, Paola Mejia Domenzain, Luca Mouchel, Tatjana Nazaretsky

Writing high-quality procedural texts is a challenging task for many learners. While example-based learning has shown promise as a feedback approach, a limitation arises when all learners receive the same content without considering their individual input ...

2024

GELEX: Generative AI-Hybrid System for Example-Based Learning

Aybars Yazici, Tanja Christina Käser Jacober, Paola Mejia Domenzain, Jibril Albachir Frej

Traditional example-based learning methods are often limited by static, expert-created content. Hence, they face challenges in scalability, engagement, and effectiveness, as some learners might struggle to relate to the examples or find them relevant. To a ...

Association for Computing Machinery2024

Teacher-Mediated and Student-Led Interaction with a Physics Simulation: Effects on the Learning Experience

Denis Gillet, Juan Carlos Farah, Jérémy Alain La Scala-Jayet

Computer simulations are often used as support material for science education, as they can engage students through inquiry-based learning, promote their active interaction in the experimentation phase, and help them visualize abstract concepts. For instanc ...

2024

Modality-invariant Visual Odometry for Embodied Vision

Amir Roshan Zamir, Roman Christian Bachmann

Effectively localizing an agent in a realistic, noisy setting is crucial for many embodied vision tasks. Visual Odometry (VO) is a practical substitute for unreliable GPS and compass sensors, especially in indoor environments. While SLAM-based methods show ...

Ieee Computer Soc2023

3D Pose Based Feedback For Physical Exercises

Pascal Fua, Mathieu Salzmann, Isinsu Katircioglu, Sena Kiciroglu

Unsupervised self-rehabilitation exercises and physical training can cause serious injuries if performed incorrectly. We introduce a learning-based framework that identifies the mistakes made by a user and proposes corrective measures for easier and safer ...

Springer2022

Temporal Pathways to Learning: How Learning Emerges in an Open-ended Collaborative Activity

Mortadha Abderrahim, Pierre Dillenbourg, Jauwairia Nasir, Aditi Kothiyal

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimo ...

2022

CrossLoc: Scalable Aerial Localization Assisted by Multimodal Synthetic Data

Jianhao Zheng, Iordan Doytchinov, Qi Yan

We present a visual localization system that learns to estimate camera poses in the real world with the help of synthetic data. Despite significant progress in recent years, most learning-based approaches to visual localization target at a single domain an ...

IEEE COMPUTER SOC2022

AI-based telepresence for broadcast applications

Rayan Daod Nathoo, Changsheng Gao, Laurent Deillon, Henrique Piñeiro Monteagudo, Touradj Ebrahimi

In this paper, we introduce a new solution and underlying architecture that allows remote participants to interact with hosts in a broadcast scenario. To achieve this, background extraction is first applied to video received from remote participants to ext ...

SPIE2022

ADA for IBL: Lessons Learned in Aligning Learning Design and Analytics for Inquiry-Based Learning Orchestration

Denis Gillet, Maria Jesus Rodriguez Triana

Orchestrating technology-enhanced learning is a difficult task, especially in demanding pedagogical approaches like inquiry-based learning (IBL). To foster effective teacher adoption, both the complexity of designing IBL activities and the uncertainty abou ...

2021

Progressive Correspondence Pruning by Consensus Learning

Mathieu Salzmann, Chen Zhao, Chenxu Zhao

Correspondence pruning aims to correctly remove false matches (outliers) from an initial set of putative correspondences. The pruning process is challenging since putative matches are typically extremely unbalanced, largely dominated by outliers, and the r ...

IEEE2021

Deep Learning Approaches for Auditory Perception in Robotics

Weipeng He

Auditory perception is an essential part of a robotic system in Human-Robot Interaction (HRI), and creating an artificial auditory perception system that is on par with human has been a long-standing goal for researchers. In fact, this is a challenging res ...

EPFL2021

GO-GA: Class Fxperiences with Offline Inquiry Learning Spaces in Go-Lab

Denis Gillet

This paper reports on a study carried out in the framework of the Go-lab Goes Africa project, in which teachers implemented online and offline Inquiry Learning Spaces (ILS) in their classes using the Go-lab platform. After a brief description of the Inquir ...

IEEE2020

Combining the Knowledge Appropriation Model and epistemic networks to understand co-creation and adoption of learning designs using log data

Denis Gillet, Maria Jesus Rodriguez Triana

Social practices are well-known mediators in the adoption of educational innovations during professional learning, as postulated by the Knowledge Appropriation Model (KAM). However, understanding how teachers adopt new pedagogical approaches at scale is of ...

2020

Social practices in teacher knowledge creation and innovation adoption: a large-scale study in an online instructional design community for inquiry learning

Denis Gillet, Maria Jesus Rodriguez Triana

Social practices are assumed to play an important role in the evolution of new teaching and learning methods. Teachers internalize knowledge developed in their communities through interactions with peers and experts while solving problems or co-creating ma ...

2020

Learning and leveraging shared domain semantics to counteract visual domain shifts

Róger Bermúdez Chacón

One of the main limitations of artificial intelligence today is its inability to adapt to unforeseen circumstances. Machine Learning (ML), due to its data-driven nature, is particularly susceptible to this. ML relies on observations in order to learn impli ...

EPFL2020

Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou

Super-resolution and denoising are ill-posed yet fundamental image restoration tasks. In blind settings, the degradation kernel or the noise level are unknown. This makes restoration even more challenging, notably for learning-based methods, as they tend t ...

2020

Efficient management of nanomaterial hazards in a large number of research laboratories in an academic environment

Thierry Meyer, Amela Groso, Anna Maria Novello, Elina Buitrago

As the number of engineered nanomaterials (ENM) used in research increases with an incredible speed, health and safety specialists are continuously faced with the challenge of evaluating the risks involved with these materials. Nowadays there is not enough ...

2020

Real-World Gait Bout Detection Using a Wrist Sensor: An Unsupervised Real-Life Validation

Kamiar Aminian, Anisoara Ionescu, Hooman Dejnabadi, Abolfazl Soltani

Gait bouts (GB), as a prominent indication of physical activity, contain valuable fundamental information closely associated with human & x2019;s health status. Therefore, objective assessment of the GB (e.g. detection, spatio-temporal analysis) during dai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Multi-View Shape Estimation of Transparent Containers

Pascal Frossard, Apostolos Modas, Andrea Cavallaro

The 3D localisation of an object and the estimation of its properties, such as shape and dimensions, are challenging under varying degrees of transparency and lighting conditions. In this paper, we propose a method for jointly localising container-like obj ...

IEEE2020

Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE

Jean-Philippe Thiran, Meritxell Bach Cuadra, Cristina Granziera, Muhamed Barakovic, Francesco La Rosa

The presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, cortic ...

2020