Concept
Visual temporal attention
Publications associées (128)
Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation
Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power.Simultaneously, a critical pain point arises as several computer vision applications are deployed ...
EPFL2024Multi-temporal forest monitoring in the Swiss Alps with knowledge-guided deep learning
Devis Tuia, Gaston Jean Lenczner, Thiên-Anh Claris Nguyen, Marc Conrad Russwurm
Monitoring forests, in particular their response to climate and land use change, requires studying long time scales. While efficient deep learning methods have been developed to process short time series of satellite imagery, leveraging long time series of ...
Elsevier Science Inc2024Saliency prediction in 360° architectural scenes: Performance and impact of daylight variations
Marilyne Andersen, Sabine Süsstrunk, Caroline Karmann, Bahar Aydemir, Kynthia Chamilothori, Seungryong Kim
Saliency models are image-based prediction models that estimate human visual attention. Such models, when applied to architectural spaces, could pave the way for design decisions where visual attention is taken into account. In this study, we tested the pe ...
2023Improving Object Detection under Domain Shifts
Object detection plays a critical role in various computer vision applications, encompassingdomains like autonomous vehicles, object tracking, and scene understanding. These applica-tions rely on detectors that generate bounding boxes around known object c ...
EPFL2023Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union
Semantic segmentation datasets often exhibit two types of imbalance: \textit{class imbalance}, where some classes appear more frequently than others and \textit{size imbalance}, where some objects occupy more pixels than others. This causes traditional eva ...
2023Text as a Richer Source of Supervision in Semantic Segmentation Tasks
Devis Tuia, Valérie Zermatten, Javiera Francisca Castillo Navarro, Lloyd Haydn Hughes
This paper introduces TACOSS a text-image alignment approach that allows explainable land cover semantic segmentation by directly integrating semantic concepts encoded from texts. TACOSS combines convolutional neural networks for visual feature extraction ...
The Institute of Electrical and Electronics Engineers, Inc2023