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20242026
most citedOpen-Canopy: Towards Very High Resolution Forest Monitoring

2 citations · 6 across the 10 of their papers we have counts for

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cs.CV2026

UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation

Yohann Perron, Guillaume Astruc, Nicolas Gonthier +2

Vision Transformers (ViT) dominate computer vision. However, their reliance on rigid patch projectors hinders transfer to Earth Observation (EO), where input modalities, scales, an…

cs.CV2025

FORMSpoT: Revealing Fine-Scale Forest Disturbances from Nation-Wide 1.5 m Forest Canopy Height Time Series

Martin Schwartz, Fajwel Fogel, Nikola Besic +9

Current large-scale satellite-based forest disturbance monitoring systems operate at 10-30~m resolution, too coarse to detect changes at the scale of individual trees and resulting…

cs.CV2025

Order Matters: 3D Shape Generation from Sequential VR Sketches

Yizi Chen, Sidi Wu, Tianyi Xiao +2

VR sketching lets users explore and iterate on ideas directly in 3D, offering a faster and more intuitive alternative to conventional CAD tools. However, existing sketch-to-shape m…

cs.CV2025

Segmenting France Across Four Centuries

Marta López-Rauhut, Hongyu Zhou, Mathieu Aubry +1

Historical maps offer an invaluable perspective into territory evolution across past centuries--long before satellite or remote sensing technologies existed. Deep learning methods…

cs.CV2025

CoDEx: Combining Domain Expertise for Spatial Generalization in Satellite Image Analysis

Abhishek Kuriyal, Elliot Vincent, Mathieu Aubry +1

Global variations in terrain appearance raise a major challenge for satellite image analysis, leading to poor model performance when training on locations that differ from those en…

cs.CV2024★ 1 cited

Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation

Nicolas Dufour, David Picard, Vicky Kalogeiton +1

Global visual geolocation predicts where an image was captured on Earth. Since images vary in how precisely they can be localized, this task inherently involves a significant degre…

cs.CV2024★ 2 cited

Open-Canopy: Towards Very High Resolution Forest Monitoring

Fajwel Fogel, Yohann Perron, Nikola Besic +8

Estimating canopy height and its changes at meter resolution from satellite imagery is a significant challenge in computer vision with critical environmental applications. However,…

cs.CV2024★ 1 cited

OpenStreetView-5M: The Many Roads to Global Visual Geolocation

Guillaume Astruc, Nicolas Dufour, Ioannis Siglidis +10

Determining the location of an image anywhere on Earth is a complex visual task, which makes it particularly relevant for evaluating computer vision algorithms. Yet, the absence of…

cs.CV2024

OmniSat: Self-Supervised Modality Fusion for Earth Observation

Guillaume Astruc, Nicolas Gonthier, Clement Mallet +1

The diversity and complementarity of sensors available for Earth Observations (EO) calls for developing bespoke self-supervised multimodal learning approaches. However, current mul…

cs.CV2024

StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation

Sidi Wu, Yizi Chen, Samuel Mermet +4

Most image-to-image translation models postulate that a unique correspondence exists between the semantic classes of the source and target domains. However, this assumption does no…

cs.CV2024★ 2 cited

Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering

Damien Robert, Hugo Raguet, Loic Landrieu

We introduce a highly efficient method for panoptic segmentation of large 3D point clouds by redefining this task as a scalable graph clustering problem. This approach can be train…