52 citations · 65 across the 8 of their papers we have counts for
4 papers · 1 filter
Leveraging Visual Question Answering to Improve Text-to-Image Synthesis
Stanislav Frolov, Shailza Jolly, Jörn Hees +1
Generating images from textual descriptions has recently attracted a lot of interest. While current models can generate photo-realistic images of individual objects such as birds a…
P NP, at least in Visual Question Answering
Shailza Jolly, Sebastian Palacio, Joachim Folz +3
In recent years, progress in the Visual Question Answering (VQA) field has largely been driven by public challenges and large datasets. One of the most widely-used of these is the…
The Wisdom of MaSSeS: Majority, Subjectivity, and Semantic Similarity in the Evaluation of VQA
Shailza Jolly, Sandro Pezzelle, Tassilo Klein +2
We introduce MASSES, a simple evaluation metric for the task of Visual Question Answering (VQA). In its standard form, the VQA task is operationalized as follows: Given an image an…
How do Convolutional Neural Networks Learn Design?
Shailza Jolly, Brian Kenji Iwana, Ryohei Kuroki +1
In this paper, we aim to understand the design principles in book cover images which are carefully crafted by experts. Book covers are designed in a unique way, specific to genres…