Ramazan Gokberk Cinbis

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Middle East Technical University

Red Carpet to Fight Club: Partially-supervised Domain Transfer for Face Recognition in Violent Videos

In many real-world problems, there is typically a large discrepancy betw...
09/16/2020 ∙ by Yunus Can Bilge, et al. ∙ 0 ∙ share

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A Deep Dive into Adversarial Robustness in Zero-Shot Learning

Machine learning (ML) systems have introduced significant advances in va...
08/17/2020 ∙ by Mehmet Kerim Yucel, et al. ∙ 0 ∙ share

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Key Protected Classification for Collaborative Learning

Large-scale datasets play a fundamental role in training deep learning m...
08/27/2019 ∙ by Mert Bülent Sarıyıldız, et al. ∙ 4 ∙ share

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Image Captioning with Unseen Objects

Image caption generation is a long standing and challenging problem at t...
07/31/2019 ∙ by Berkan Demirel, et al. ∙ 2 ∙ share

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Zero-Shot Sign Language Recognition: Can Textual Data Uncover Sign Languages?

We introduce the problem of zero-shot sign language recognition (ZSSLR),...
07/24/2019 ∙ by Yunus Can Bilge, et al. ∙ 10 ∙ share

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Learning Visually Consistent Label Embeddings for Zero-Shot Learning

In this work, we propose a zero-shot learning method to effectively mode...
05/16/2019 ∙ by Berkan Demirel, et al. ∙ 0 ∙ share

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Cross-task weakly supervised learning from instructional videos

In this paper we investigate learning visual models for the steps of ord...
03/19/2019 ∙ by Dimitri Zhukov, et al. ∙ 4 ∙ share

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Multisource Region Attention Network for Fine-Grained Object Recognition in Remote Sensing Imagery

Fine-grained object recognition concerns the identification of the type ...
01/18/2019 ∙ by Gencer Sumbul, et al. ∙ 6 ∙ share

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Wildest Faces: Face Detection and Recognition in Violent Settings

With the introduction of large-scale datasets and deep learning models c...
05/19/2018 ∙ by Mehmet Kerim Yucel, et al. ∙ 0 ∙ share

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Zero-Shot Object Detection by Hybrid Region Embedding

Object detection is considered as one of the most challenging problems i...
05/16/2018 ∙ by Berkan Demirel, et al. ∙ 4 ∙ share

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Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery

Fine-grained object recognition that aims to identify the type of an obj...
12/09/2017 ∙ by Gencer Sumbul, et al. ∙ 0 ∙ share

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Attributes2Classname: A discriminative model for attribute-based unsupervised zero-shot learning

We propose a novel approach for unsupervised zero-shot learning (ZSL) of...
05/04/2017 ∙ by Berkan Demirel, et al. ∙ 0 ∙ share

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Approximate Fisher Kernels of non-iid Image Models for Image Categorization

The bag-of-words (BoW) model treats images as sets of local descriptors ...
10/03/2015 ∙ by Ramazan Gokberk Cinbis, et al. ∙ 0 ∙ share

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Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning

Object category localization is a challenging problem in computer vision...
03/03/2015 ∙ by Ramazan Gokberk Cinbis, et al. ∙ 0 ∙ share

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Ramazan Gokberk Cinbis

Featured Co-authors

Cordelia Schmid

Ivan Laptev

Josef Sivic

Jakob Verbeek

Jean-Baptiste Alayrac

Gencer Sumbul

Erman Ayday

Pinar Duygulu

Nazli Ikizler-Cinbis

David Fouhey

Berkan Demirel

Red Carpet to Fight Club: Partially-supervised Domain Transfer for Face Recognition in Violent Videos

A Deep Dive into Adversarial Robustness in Zero-Shot Learning

Key Protected Classification for Collaborative Learning

Image Captioning with Unseen Objects

Zero-Shot Sign Language Recognition: Can Textual Data Uncover Sign Languages?

Learning Visually Consistent Label Embeddings for Zero-Shot Learning

Cross-task weakly supervised learning from instructional videos

Multisource Region Attention Network for Fine-Grained Object Recognition in Remote Sensing Imagery

Wildest Faces: Face Detection and Recognition in Violent Settings

Zero-Shot Object Detection by Hybrid Region Embedding

Fine-Grained Object Recognition and Zero-Shot Learning in Remote Sensing Imagery

Attributes2Classname: A discriminative model for attribute-based unsupervised zero-shot learning

Approximate Fisher Kernels of non-iid Image Models for Image Categorization

Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning