Zeynep Akata (Senior Researcher)
Personal Information
Zeynep Akata holds a double affiliation as Senior Researcher at the MPI for Informatics leading the Multimodal Deep Learning group, and as Assistant Professor at the University of Amsterdam where she is the scientific manager of the Delta Lab. Her research focuses on deep learning, representation learning, semi-supervised learning, generative modeling of multi-modal data and large-scale learning.
Overview of my research while at MPI (2015-2017) and CV
For prospecive students/members: I do not have PhD or Post-doc openings this year.
Education
- PhD: INRIA Rhone Alpes, Université de Grenoble, France, 2011-2014
- MSc: Media Informatics, RWTH Aachen, Germany, 2008-2010
- BSc: Computer Science, Trakya University, Turkey, 2004-2008
Teaching
- High-Level Computer Vision (SS2014), teaching assistant
- Tutorial on Embeddings and its Applications, GCPR 2016
Students
- Mr. Yongqin Xian, Completed MSc with Honors (2015), now PhD student
- Ms. Nour Karessli, Completed MSc (2016), now Research Scientist at Eyeem
- Mr. Jiayi Wang, Research Immersion Lab (2017)
Awards
- Best Reviewer Award, CVPR 2016, ECCV 2016
- Lise Meitner Award, Max Planck Institute, 2014
- PhD Scholarship: CIFRE, ANRT France, 2011
- Best Poster Award: INRIA CVML Summer School, 2010
- MSc Scholarship: TUBITAK Turkey, 2008
- Faculty and Department Rank 1 in BSc Graduation, 2008
External Activities
- Reviewer in Journals: TPAMI 2015-, IJCV 2015-
- Reviewer in Conferences: NIPS 2016--, ICCV 2015--, CVPR 2015--, ECCV 2016--, ACCV 2016, AISTATS 2017
- Area Chair: WACV 2016
- Tutorial on Zero-Shot Learning, CVPR 2017, Organization Committee
- Tutorial on Embeddings and Metric Learning, GCPR 2016, Organization Committee
- Gender Diversity in STEM fields, Springboard training program, 2015, Organization Committee
- Lise Meitner Award Fellowship for Excellent Women in Computer Science 2016, Organization Committee
Publications
Gaze Embeddings for Zero-Shot Image Classification
Nour Karessli, Zeynep Akata, Bernt Schiele, Andreas Bulling
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 (Spotlight Presentation)
Zero-Shot Learning - The Good, the Bad and the Ugly
Yongqin Xian, Bernt Schiele, Zeynep Akata
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
Exploiting saliency for object segmentation from image level labels
Seong Joon Oh, Rodrigo Benenson, Anna Khoreva, Zeynep Akata, Mario Fritz, Bernt Schiele
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017
Learning What and Where to Draw
Scott Reed, Zeynep Akata, Santosh Mohan, Samuel Tenka, Bernt Schiele and Honglak Lee
Neural Information Processing Systems, NIPS 2016(Oral Presentation)
Generating Visual Explanations
Lisa Hendricks, Zeynep Akata, Marcus Rohrbach, Jeff Donahue, Bernt Schiele and Trevor Darrell
European Conference of Computer Vision, ECCV 2016
Generative Adversarial Text to Image Synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Honglak Lee and Bernt Schiele
International Conference of Machine Learning, ICML 2016(Oral Presentation)
Learning Deep Representations of Fine-Grained Visual Descriptions
Scott Reed, Zeynep Akata, Honglak Lee and Bernt Schiele
IEEE Conference of Computer Vision and Patter Recognition, CVPR 2016(Spotlight Presentation)
Multi-Cue Zero-Shot Learning with Strong Supervision
Zeynep Akata, Mateusz Malinowski, Mario Fritz and Bernt Schiele
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 (Spotlight Presentation)
Latent Embeddings for Zero-Shot Classification
Yongqin Xian, Zeynep Akata, Gaurav Sharma, Quynh Nguyen, Matthias Hein and Bernt Schiele
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016 (Spotlight Presentation)
Evaluation of Output Embeddings for Image Classification
Zeynep Akata, Scott Reed, Daniel Walter, Honglak Lee and Bernt Schiele
IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
Label Embeddings for Image Classification
Zeynep Akata, Florent Perronnin, Zaid Harchaoui, Cordelia Schmid
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), Vol:38, No:7, July 2016
Publications before MPI
- Label Embedding View of Attribute Based Recognition, United States Patent Application, No: 13/923639, Publication date: 12/25/2014
- Good Practice in Large-Scale Learning for Image Classification, Z. Akata, F. Perronnin, Z. Harchaoui and C. Schmid, IEEE TPAMI 2014
- Contributions to large-scale learning for image classification, Z. Akata, PhD Thesis, INRIA Grenoble, 2014
- Attribute-Based Classification with Label-Embedding, Z. Akata, F. Perronnin, Z. Harchaoui and C. Schmid, ORL, NIPS Workshop, 2013
- Label-Embedding for Attribute-Based Classification, Z. Akata, F. Perronnin, Z. Harchaoui and C. Schmid, IEEE CVPR 2013
- Towards Good Practice in Large-Scale Learning for Image Classification, F. Perronnin, Z. Akata, Z. Harchaoui and C. Schmid, IEEE CVPR 2012
- Non-negative Matrix Factorization in Multimodality Data for Segmentation and Label Prediction, Z. Akata, C. Thurau and C. Bauckhage, CVWW 2011