2 citations · 2 across the 7 of their papers we have counts for
7 papers
Beyond Gaussian Worlds: Latent Geometry Matters for JEPAs
Léo Nicollier, Enric Meinhardt-Llopis, Marc Pic +2
Recent Joint-Embedding Predictive Architectures (JEPAs) prevent representation collapse by constraining learned representations to follow a prescribed target distribution, such as…
Unbiased Open World Regularization for Fair Self-Supervised Learning
L{é}o Nicollier, Marc Pic, Pablo Mus{é} +2
Despite recent advances, self-supervised learning (SSL) models and Joint-Embedding Predictive Architectures (JEPAs) remain susceptible to learning spurious biases in the dataset. T…
An Industrial Dataset for Scene Acquisitions and Functional Schematics Alignment
Flavien Armangeon, Thibaud Ehret, Enric Meinhardt-Llopis +4
Aligning functional schematics with 2D and 3D scene acquisitions is crucial for building digital twins, especially for old industrial facilities that lack native digital models. Cu…
Beyond Paired Data: Self-Supervised UAV Geo-Localization from Reference Imagery Alone
Tristan Amadei, Enric Meinhardt-Llopis, Benedicte Bascle +2
Image-based localization in GNSS-denied environments is critical for UAV autonomy. Existing state-of-the-art approaches rely on matching UAV images to geo-referenced satellite imag…
S-EO: A Large-Scale Dataset for Geometry-Aware Shadow Detection in Remote Sensing Applications
Elías Masquil, Roger Marí, Thibaud Ehret +3
We introduce the S-EO dataset: a large-scale, high-resolution dataset, designed to advance geometry-aware shadow detection. Collected from diverse public-domain sources, including…
Automatic Stockpile Volume Monitoring using Multi-view Stereo from SkySat Imagery
Roger Marí, Carlo de Franchis, Enric Meinhardt-Llopis +1
This paper proposes a system for automatic surface volume monitoring from time series of SkySat pushframe imagery. A specific challenge of building and comparing large 3D models fr…
FALDOI: A new minimization strategy for large displacement variational optical flow
Roberto P. Palomares, Enric Meinhardt-Llopis, Coloma Ballester +1
We propose a large displacement optical flow method that introduces a new strategy to compute a good local minimum of any optical flow energy functional. The method requires a give…