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Found 7 papers, 1 papers with code
Exploring Robust Features for Few-Shot Object Detection in Satellite Imagery
Moreover, we study the performance of both visual and image-text features, namely DINOv2 and CLIP, including two CLIP models specifically tailored for remote sensing applications.
Portraying the Need for Temporal Data in Flood Detection via Sentinel-1
Identifying flood affected areas in remote sensing data is a critical problem in earth observation to analyze flood impact and drive responses.
Reducing False Alarms in Video Surveillance by Deep Feature Statistical Modeling
Experimental results reveal that the proposed a-contrario validation is able to largely reduce the number of false alarms at both pixel and object levels.
The whole and the parts: the MDL principle and the a-contrario framework
This work explores the connections between the Minimum Description Length (MDL) principle as developed by Rissanen, and the a-contrario framework for structure detection proposed by Desolneux, Moisan and Morel.
Psychophysics, Gestalts and Games
Using a computational quantitative version of the non-accidentalness principle, we raise the possibility that the psychophysical and the (older) gestaltist setups, both applicable on dot or Gabor patterns, find a useful complement in a Turing test.
From line segments to more organized Gestalts
In this paper, we reconsider the early computer vision bottom-up program, according to which higher level features (geometric structures) in an image could be built up recursively from elementary features by simple grouping principles coming from Gestalt theory.
Finding Vanishing Points via Point Alignments in Image Primal and Dual Domains
We present a novel method for automatic vanishing point detection based on primal and dual point alignment detection.
