2 citations · 6 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
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,…
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…
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…
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…
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…