6 citations · 7 across the 6 of their papers we have counts for
6 papers
A Multimodal Recaptioning Framework to Account for Perceptual Diversity Across Languages in Vision-Language Modeling
Kyle Buettner, Jacob T. Emmerson, Adriana Kovashka
When captioning an image, people describe objects in diverse ways, such as by using different terms and/or including details that are perceptually noteworthy to them. Descriptions…
Quantifying the Gaps Between Translation and Native Perception in Training for Multimodal, Multilingual Retrieval
Kyle Buettner, Adriana Kovashka
There is a scarcity of multilingual vision-language models that properly account for the perceptual differences that are reflected in image captions across languages and cultures.…
Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition
Kyle Buettner, Sina Malakouti, Xiang Lorraine Li +1
Existing object recognition models have been shown to lack robustness in diverse geographical scenarios due to domain shifts in design and context. Class representations need to be…
Investigating the Role of Attribute Context in Vision-Language Models for Object Recognition and Detection
Kyle Buettner, Adriana Kovashka
Vision-language alignment learned from image-caption pairs has been shown to benefit tasks like object recognition and detection. Methods are mostly evaluated in terms of how well…
Contrastive View Design Strategies to Enhance Robustness to Domain Shifts in Downstream Object Detection
Kyle Buettner, Adriana Kovashka
Contrastive learning has emerged as a competitive pretraining method for object detection. Despite this progress, there has been minimal investigation into the robustness of contra…
Story Understanding in Video Advertisements
Keren Ye, Kyle Buettner, Adriana Kovashka
In order to resonate with the viewers, many video advertisements explore creative narrative techniques such as "Freytag's pyramid" where a story begins with exposition, followed by…