3 citations · 5 across the 5 of their papers we have counts for
5 papers
MULAN: A Multi Layer Annotated Dataset for Controllable Text-to-Image Generation
Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang +5
Text-to-image generation has achieved astonishing results, yet precise spatial controllability and prompt fidelity remain highly challenging. This limitation is typically addressed…
Learning to Name Classes for Vision and Language Models
Sarah Parisot, Yongxin Yang, Steven McDonagh
Large scale vision and language models can achieve impressive zero-shot recognition performance by mapping class specific text queries to image content. Two distinct challenges tha…
Long-tail Recognition via Compositional Knowledge Transfer
Sarah Parisot, Pedro M. Esperanca, Steven McDonagh +3
In this work, we introduce a novel strategy for long-tail recognition that addresses the tail classes' few-shot problem via training-free knowledge transfer. Our objective is to tr…
Proceedings of the Workshop on Brain Analysis using COnnectivity Networks - BACON 2016
Sarah Parisot, Jonathan Passerat-Palmbach, Markus D. Schirmer +1
Understanding brain connectivity in a network-theoretic context has shown much promise in recent years. This type of analysis identifies brain organisational principles, bringing a…
Comparison of Brain Networks with Unknown Correspondences
Sofia Ira Ktena, Sarah Parisot, Jonathan Passerat-Palmbach +1
Graph theory has drawn a lot of attention in the field of Neuroscience during the last decade, mainly due to the abundance of tools that it provides to explore the interactions of…