5 papers
Will It Zero-Shot?: Predicting Zero-Shot Classification Performance For Arbitrary Queries
Kevin Robbins, Xiaotong Liu, Yu Wu +4
Vision-Language Models like CLIP create aligned embedding spaces for text and images, making it possible for anyone to build a visual classifier by simply naming the classes they w…
QuARI: Query Adaptive Retrieval Improvement
Eric Xing, Abby Stylianou, Robert Pless +1
Massive-scale pretraining has made vision-language models increasingly popular for image-to-image and text-to-image retrieval across a broad collection of domains. However, these m…
ConText-CIR: Learning from Concepts in Text for Composed Image Retrieval
Eric Xing, Pranavi Kolouju, Robert Pless +2
Composed image retrieval (CIR) is the task of retrieving a target image specified by a query image and a relative text that describes a semantic modification to the query image. Ex…
good4cir: Generating Detailed Synthetic Captions for Composed Image Retrieval
Pranavi Kolouju, Eric Xing, Robert Pless +2
Composed image retrieval (CIR) enables users to search images using a reference image combined with textual modifications. Recent advances in vision-language models have improved C…
Design and Evaluation of Camera-Centric Mobile Crowdsourcing Applications
Abby Stylianou, Michelle Brachman, Albatool Wazzan +2
The data that underlies automated methods in computer vision and machine learning, such as image retrieval and fine-grained recognition, often comes from crowdsourcing. In contexts…