22k citations · 25.7k across the 25 of their papers we have counts for
5 papers · 2 filters
Combining Multiple Cues for Visual Madlibs Question Answering
Tatiana Tommasi, Arun Mallya, Bryan Plummer +3
This paper presents an approach for answering fill-in-the-blank multiple choice questions from the Visual Madlibs dataset. Instead of generic and commonly used representations trai…
Fast Single Shot Detection and Pose Estimation
Patrick Poirson, Phil Ammirato, Cheng-Yang Fu +3
For applications in navigation and robotics, estimating the 3D pose of objects is as important as detection. Many approaches to pose estimation rely on detecting or tracking parts…
When was that made?
Sirion Vittayakorn, Alexander C. Berg, Tamara L. Berg
In this paper, we explore deep learning methods for estimating when objects were made. Automatic methods for this task could potentially be useful for historians, collectors, or an…
Solving Visual Madlibs with Multiple Cues
Tatiana Tommasi, Arun Mallya, Bryan Plummer +3
This paper focuses on answering fill-in-the-blank style multiple choice questions from the Visual Madlibs dataset. Previous approaches to Visual Question Answering (VQA) have mainl…
Modeling Context in Referring Expressions
Licheng Yu, Patrick Poirson, Shan Yang +2
Humans refer to objects in their environments all the time, especially in dialogue with other people. We explore generating and comprehending natural language referring expressions…