Rakshith Shetty (PhD Student)

MSc Rakshith Shetty
- Address
- Max-Planck-Institut für Informatik
Saarland Informatics Campus
Campus - Location
- -
- Phone
- +49 681 9325 2000
- Fax
- +49 681 9325 2099
- Get email via email
Publications
2020
Diverse and Relevant Visual Storytelling with Scene Graph Embeddings
X. Hong, R. Shetty, A. Sayeed, K. Mehra, V. Demberg and B. Schiele
Proceedings of the 24th Conference on Computational Natural Language Learning (CoNLL 2020), 2020
X. Hong, R. Shetty, A. Sayeed, K. Mehra, V. Demberg and B. Schiele
Proceedings of the 24th Conference on Computational Natural Language Learning (CoNLL 2020), 2020
2019
2018
Adversarial Scene Editing: Automatic Object Removal from Weak Supervision
R. Shetty, M. Fritz and B. Schiele
Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 2018
R. Shetty, M. Fritz and B. Schiele
Advances in Neural Information Processing Systems 31 (NeurIPS 2018), 2018
Abstract
While great progress has been made recently in automatic image manipulation,
it has been limited to object centric images like faces or structured scene
datasets. In this work, we take a step towards general scene-level image
editing by developing an automatic interaction-free object removal model. Our
model learns to find and remove objects from general scene images using
image-level labels and unpaired data in a generative adversarial network (GAN)
framework. We achieve this with two key contributions: a two-stage editor
architecture consisting of a mask generator and image in-painter that
co-operate to remove objects, and a novel GAN based prior for the mask
generator that allows us to flexibly incorporate knowledge about object shapes.
We experimentally show on two datasets that our method effectively removes a
wide variety of objects using weak supervision only
A4NT: Author Attribute Anonymity by Adversarial Training of Neural Machine Translation
R. Shetty, B. Schiele and M. Fritz
Proceedings of the 27th USENIX Security Symposium, 2018
R. Shetty, B. Schiele and M. Fritz
Proceedings of the 27th USENIX Security Symposium, 2018
2017