21 citations · 44 across the 6 of their papers we have counts for
8 papers
Comparing Traditional and LLM-based Search for Image Geolocation
Albatool Wazzan, Stephen MacNeil, Richard Souvenir
Web search engines have long served as indispensable tools for information retrieval; user behavior and query formulation strategies have been well studied. The introduction of sea…
Federated Compositional Deep AUC Maximization
Xinwen Zhang, Yihan Zhang, Tianbao Yang +2
Federated learning has attracted increasing attention due to the promise of balancing privacy and large-scale learning; numerous approaches have been proposed. However, most existi…
TraffickCam: Explainable Image Matching For Sex Trafficking Investigations
Abby Stylianou, Richard Souvenir, Robert Pless
Investigations of sex trafficking sometimes have access to photographs of victims in hotel rooms. These images directly link victims to places, which can help verify where victims…
Hotels-50K: A Global Hotel Recognition Dataset
Abby Stylianou, Hong Xuan, Maya Shende +3
Recognizing a hotel from an image of a hotel room is important for human trafficking investigations. Images directly link victims to places and can help verify where victims have b…
Visualizing Deep Similarity Networks
Abby Stylianou, Richard Souvenir, Robert Pless
For convolutional neural network models that optimize an image embedding, we propose a method to highlight the regions of images that contribute most to pairwise similarity. This w…
Deep Randomized Ensembles for Metric Learning
Hong Xuan, Richard Souvenir, Robert Pless
Learning embedding functions, which map semantically related inputs to nearby locations in a feature space supports a variety of classification and information retrieval tasks. In…
Understanding and Mapping Natural Beauty
Scott Workman, Richard Souvenir, Nathan Jacobs
While natural beauty is often considered a subjective property of images, in this paper, we take an objective approach and provide methods for quantifying and predicting the scenic…
Wide-Area Image Geolocalization with Aerial Reference Imagery
Scott Workman, Richard Souvenir, Nathan Jacobs
We propose to use deep convolutional neural networks to address the problem of cross-view image geolocalization, in which the geolocation of a ground-level query image is estimated…