no code implementations • 2 May 2022 • AJ Piergiovanni, Wei Li, Weicheng Kuo, Mohammad Saffar, Fred Bertsch, Anelia Angelova
We present Answer-Me, a task-aware multi-task framework which unifies a variety of question answering tasks, such as, visual question answering, visual entailment, visual reasoning.
no code implementations • 31 Mar 2022 • Weicheng Kuo, Fred Bertsch, Wei Li, AJ Piergiovanni, Mohammad Saffar, Anelia Angelova
We propose FindIt, a simple and versatile framework that unifies a variety of visual grounding and localization tasks including referring expression comprehension, text-based localization, and object detection.
1 code implementation • 13 May 2021 • Trung Le, Ryan Poplin, Fred Bertsch, Andeep Singh Toor, Margaret L. Oh
We introduce a new dataset called SyntheticFur built specifically for machine learning training.
no code implementations • 13 Feb 2018 • Natasha Jaques, Jennifer McCleary, Jesse Engel, David Ha, Fred Bertsch, Rosalind Picard, Douglas Eck
We use a Latent Constraints GAN (LC-GAN) to learn from the facial feedback of a small group of viewers, by optimizing the model to produce sketches that it predicts will lead to more positive facial expressions.
4 code implementations • ICLR 2018 • Amélie Royer, Konstantinos Bousmalis, Stephan Gouws, Fred Bertsch, Inbar Mosseri, Forrester Cole, Kevin Murphy
Style transfer usually refers to the task of applying color and texture information from a specific style image to a given content image while preserving the structure of the latter.
no code implementations • ICLR 2018 • Andrew Kyle Lampinen, David So, Douglas Eck, Fred Bertsch
GANs provide a framework for training generative models which mimic a data distribution.