3 citations · 4 across the 11 of their papers we have counts for
14 papers
Are In-Context Images Worth 10 Dimensions?
Adhemar de Senneville, Xavier Bou, Jérémy Anger +2
There has been significant work on understanding the In-Context Learning capabilities of Large Language Models, especially on the induction circuit. For a few-shot classification t…
Unlocking Few-Shot Capabilities in LVLMs via Prompt Conditioning and Head Selection
Adhemar de Senneville, Xavier Bou, Jérémy Anger +2
Current Large Vision Language Models (LVLMs) excel at many zero-shot tasks like image captioning, visual question answering and OCR. However, these same models suffer from poor per…
Comparative analysis of dual-form networks for live land monitoring using multi-modal satellite image time series
Iris Dumeur, Jérémy Anger, Gabriele Facciolo
Multi-modal Satellite Image Time Series (SITS) analysis faces significant computational challenges for live land monitoring applications. While Transformer architectures excel at c…
Normalized vs Diplomatic Annotation: A Case Study of Automatic Information Extraction from Handwritten Uruguayan Birth Certificates
Natalia Bottaioli, Solène Tarride, Jérémy Anger +8
This study evaluates the recently proposed Document Attention Network (DAN) for extracting key-value information from Uruguayan birth certificates, handwritten in Spanish. We inves…
Portraying the Need for Temporal Data in Flood Detection via Sentinel-1
Xavier Bou, Thibaud Ehret, Rafael Grompone von Gioi +1
Identifying flood affected areas in remote sensing data is a critical problem in earth observation to analyze flood impact and drive responses. While a number of methods have been…
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image Super-Resolution of Sentinel-2 L1B Imagery
Ngoc Long Nguyen, Jérémy Anger, Axel Davy +2
High-resolution satellite imagery is a key element for many Earth monitoring applications. Satellites such as Sentinel-2 feature characteristics that are favorable for super-resolu…
On The Role of Alias and Band-Shift for Sentinel-2 Super-Resolution
Ngoc Long Nguyen, Jérémy Anger, Lara Raad +2
In this work, we study the problem of single-image super-resolution (SISR) of Sentinel-2 imagery. We show that thanks to its unique sensor specification, namely the inter-band shif…
Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites
Ngoc Long Nguyen, Jérémy Anger, Axel Davy +2
Modern Earth observation satellites capture multi-exposure bursts of push-frame images that can be super-resolved via computational means. In this work, we propose a super-resoluti…
Parallax estimation for push-frame satellite imagery: application to super-resolution and 3D surface modeling from Skysat products
Jérémy Anger, Thibaud Ehret, Gabriele Facciolo
Recent constellations of satellites, including the Skysat constellation, are able to acquire bursts of images. This new acquisition mode allows for modern image restoration techniq…
Proba-V-ref: Repurposing the Proba-V challenge for reference-aware super resolution
Ngoc Long Nguyen, Jérémy Anger, Axel Davy +2
The PROBA-V Super-Resolution challenge distributes real low-resolution image series and corresponding high-resolution targets to advance research on Multi-Image Super Resolution (M…
Self-Supervised training for blind multi-frame video denoising
Valéry Dewil, Jérémy Anger, Axel Davy +3
We propose a self-supervised approach for training multi-frame video denoising networks. These networks predict frame t from a window of frames around t. Our self-supervised approa…
Efficient Blind Deblurring under High Noise Levels
Jérémy Anger, Mauricio Delbracio, Gabriele Facciolo
The goal of blind image deblurring is to recover a sharp image from a motion blurred one without knowing the camera motion. Current state-of-the-art methods have a remarkably good…
Assessing the Sharpness of Satellite Images: Study of the PlanetScope Constellation
Jérémy Anger, Carlo de Franchis, Gabriele Facciolo
New micro-satellite constellations enable unprecedented systematic monitoring applications thanks to their wide coverage and short revisit capabilities. However, the large volumes…
Modeling Realistic Degradations in Non-blind Deconvolution
Jérémy Anger, Mauricio Delbracio, Gabriele Facciolo
Most image deblurring methods assume an over-simplistic image formation model and as a result are sensitive to more realistic image degradations. We propose a novel variational fra…