Explore the words cloud of the DeepFace project. It provides you a very rough idea of what is the project "DeepFace" about.
The following table provides information about the project.
Coordinator |
TEL AVIV UNIVERSITY
Organization address contact info |
Coordinator Country | Israel [IL] |
Total cost | 1˙696˙888 € |
EC max contribution | 1˙696˙888 € (100%) |
Programme |
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC)) |
Code Call | ERC-2016-COG |
Funding Scheme | ERC-COG |
Starting year | 2017 |
Duration (year-month-day) | from 2017-05-01 to 2022-04-30 |
Take a look of project's partnership.
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1 | TEL AVIV UNIVERSITY | IL (TEL AVIV) | coordinator | 1˙696˙888.00 |
Face recognition is a fascinating domain: no other domain seems to present as much value when analysing casual photos; it is one of the few domains in machine learning in which millions of classes are routinely learned; and the trade-off between subtle inter-identity variations and pronounced intra-identity variations forms a unique challenge.
The advent of deep learning has brought machines to what is considered a human level of performance. However, there are many research questions that are left open. At the top most level, we ask two questions: what is unique about faces in comparison to other recognition tasks that also employ deep networks and how can we make the next leap in performance of automatic face recognition?
We consider three domains of research. The first is the study of methods that promote effective transfer learning. This is crucial since all state of the art face recognition methods rely on transfer learning. The second domain is the study of the tradeoffs that govern the optimal utilization of the training data and how the properties of the training data affect the optimal network design. The third domain is the post transfer utilization of the learned deep networks, where given the representations of a pair of face images, we seek to compare them in the most accurate way.
Throughout this proposal, we put an emphasis on theoretical reasoning. I aim to support the developed methods by a theoretical framework that would both justify their usage as well as provide concrete guidelines for using them. My goal of achieving a leap forward in performance through a level of theoretical analysis that is unparalleled in object recognition, makes our research agenda truly high-risk/ high-gains. I have been in the forefront of face recognition for the last 8 years and my lab's recent achievements in deep learning suggest that we will be able to carry out this research. To further support its feasibility, we present very promising initial results.
year | authors and title | journal | last update |
---|---|---|---|
2019 |
Benjamin Klein
Lior Wolf End-to-End Supervised Product Quantization for Image Search and Retrieval published pages: , ISSN: , DOI: |
2019-12-16 | |
2020 |
W-J. Nam, Shir Gur, J. Choi, Lior Wolf, S-W. Lee. Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks published pages: , ISSN: , DOI: |
AAAI | 2019-12-16 |
2017 |
Benaim, Sagie; Wolf, Lior One-Sided Unsupervised Domain Mapping published pages: , ISSN: , DOI: |
NIPS | 2019-12-16 |
2019 |
Gur, Shir; Wolf, Lior; Golgher, Lior; Blinder, Pablo Unsupervised Microvascular Image Segmentation Using an Active Contours Mimicking Neural Network published pages: , ISSN: , DOI: |
ICCV | 2019-12-16 |
2019 |
Shir Gur
Lior Wolf Single Image Depth Estimation Trained via Depth from Defocus Cues published pages: , ISSN: , DOI: |
2019-12-16 | |
2018 |
Galanti, Tomer; Benaim, Sagie; Wolf, Lior Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs published pages: , ISSN: , DOI: |
arXiv preprint 1 | 2019-12-16 |
2019 |
Tomer Cohen
Lior Wolf Bidirectional One-Shot Unsupervised Domain Mapping published pages: , ISSN: , DOI: |
ICCV | 2019-12-16 |
2020 |
Eyal Shulman
Lior Wolf Meta Decision Trees for Explainable Recommendation Systems published pages: , ISSN: , DOI: |
Artificial Intelligence, Ethics, and Society (AIES) | 2019-12-16 |
2019 |
Littwin, Gidi; Wolf, Lior Deep Meta Functionals for Shape Representation published pages: , ISSN: , DOI: |
ICCV | 2019-12-16 |
2019 |
Sagie Benaim
Michael Khaitov
Tomer Galanti
Lior Wolf Domain Intersection and Domain Difference. published pages: , ISSN: , DOI: |
2019-12-16 | |
2019 |
Oron Ashual
Lior Wolf Specifying Object Attributes and Relations in Interactive Scene Generation. published pages: , ISSN: , DOI: |
ICCV | 2019-12-16 |
2019 |
Etai Littwin, Lior Wolf On the Convex Behavior of Deep Neural Networks in Relation to the Layers\' Width published pages: , ISSN: , DOI: |
ICML 2019 Workshop Deep Phenomena homepage | 2019-12-16 |
2017 |
Klein, Benjamin; Wolf, Lior In Defense of Product Quantization published pages: , ISSN: , DOI: |
arXiv preprint 2 | 2019-05-23 |
2018 |
Benaim, Sagie; Wolf, Lior One-Shot Unsupervised Cross Domain Translation published pages: , ISSN: , DOI: |
NIPS 1 | 2019-05-23 |
2019 |
L. Wolf, S. Benaim, T. Galanti. Unsupervised Learning of the Set of Local Maxima. International Conference on Learning Representations (ICLR), 2019. published pages: , ISSN: , DOI: |
ICLR | 2019-02-26 |
2018 |
Tomer Galanti, Lior Wolf Generalization Bounds for Unsupervised Cross-Domain Mapping with WGANs. published pages: , ISSN: , DOI: |
Integration of Deep Learning Theories NIPS workshop | 2019-02-26 |
2018 |
Lior Wolf; Etai Littwin Regularizing by the Variance of the Activations\' Sample-Variances published pages: , ISSN: , DOI: |
NIPS | 2019-02-26 |
2018 |
Doron Sobol, Lior Wolf, Yaniv Taigman Visual analogies between Atari games for studying transfer learning published pages: , ISSN: , DOI: |
arXiv preprint | 2019-02-26 |
2018 |
Galanti, Tomer; Wolf, Lior; Benaim, Sagie The Role of Minimal Complexity Functions in Unsupervised Learning of Semantic Mappings published pages: , ISSN: , DOI: |
ICLR 2 | 2019-02-26 |
2019 |
L. Wolf, T. Galanti, T. Hazan A Formal Approach to Explainability. published pages: , ISSN: , DOI: |
Artificial Intelligence, Ethics, and Society (AIES) | 2019-02-26 |
2019 |
O. Press, T. Galanti, S. Benaim, L. Wolf Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer. published pages: , ISSN: , DOI: |
ICLR | 2019-02-26 |
Are you the coordinator (or a participant) of this project? Plaese send me more information about the "DEEPFACE" project.
For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.
Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.
Thanks. And then put a link of this page into your project's website.
The information about "DEEPFACE" are provided by the European Opendata Portal: CORDIS opendata.
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