2 citations · 2 across the 3 of their papers we have counts for
7 papers
Weakly-Supervised Action Detection Guided by Audio Narration
Keren Ye, Adriana Kovashka
Videos are more well-organized curated data sources for visual concept learning than images. Unlike the 2-dimensional images which only involve the spatial information, the additio…
Linguistic Structures as Weak Supervision for Visual Scene Graph Generation
Keren Ye, Adriana Kovashka
Prior work in scene graph generation requires categorical supervision at the level of triplets - subjects and objects, and predicates that relate them, either with or without bound…
SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection
Keren Ye, Adriana Kovashka, Mark Sandler +3
Deep learning based object detectors are commonly deployed on mobile devices to solve a variety of tasks. For maximum accuracy, each detector is usually trained to solve one single…
Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection
Keren Ye, Mingda Zhang, Adriana Kovashka +3
Learning to localize and name object instances is a fundamental problem in vision, but state-of-the-art approaches rely on expensive bounding box supervision. While weakly supervis…
Learning to discover and localize visual objects with open vocabulary
Keren Ye, Mingda Zhang, Wei Li +3
To alleviate the cost of obtaining accurate bounding boxes for training today's state-of-the-art object detection models, recent weakly supervised detection work has proposed techn…
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…