4 papers · 1 filter
Counting Trees from Satellite Imagery with Noisy Supervision
Dimitri Gominski, Maurice Mugabowindekwe, Qiue Xu +6
Counting individual trees is a fundamental task for environmental monitoring, yet remains largely unexplored with satellite imagery. At these resolutions, isolated trees may still…
Who Needs Labels? Adapting Vision Foundation Models With the Metadata You Already Have
Elouan Gardès, Seung Eun Yi, Kartik Ahuja +6
We propose a label-free approach to adapt powerful but generic vision foundation models to specialized scientific domains. Standard supervised fine-tuning is often ill-suited to th…
PoM: A Linear-Time Replacement for Attention with the Polynomial Mixer
David Picard, Nicolas Dufour, Lucas Degeorge +14
This paper introduces the Polynomial Mixer (PoM), a novel token mixing mechanism with linear complexity that serves as a drop-in replacement for self-attention. PoM aggregates inpu…
Adapting Vision Transformers to Ultra-High Resolution Semantic Segmentation with Relay Tokens
Yohann Perron, Vladyslav Sydorov, Christophe Pottier +1
Current approaches for segmenting ultra high resolution images either slide a window, thereby discarding global context, or downsample and lose fine detail. We propose a simple yet…