59 citations · 133 across the 12 of their papers we have counts for
14 papers
Multi-Contrast MRI Segmentation Trained on Synthetic Images
Ismail Irmakci, Zeki Emre Unel, Nazli Ikizler-Cinbis +1
In our comprehensive experiments and evaluations, we show that it is possible to generate multiple contrast (even all synthetically) and use synthetically generated images to train…
Towards Zero-shot Sign Language Recognition
Yunus Can Bilge, Ramazan Gokberk Cinbis, Nazli Ikizler-Cinbis
This paper tackles the problem of zero-shot sign language recognition (ZSSLR), where the goal is to leverage models learned over the seen sign classes to recognize the instances of…
MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation
Mustafa Sercan Amac, Ahmet Sencan, Orhun Bugra Baran +2
Just like other few-shot learning problems, few-shot segmentation aims to minimize the need for manual annotation, which is particularly costly in segmentation tasks. Even though t…
Red Carpet to Fight Club: Partially-supervised Domain Transfer for Face Recognition in Violent Videos
Yunus Can Bilge, Mehmet Kerim Yucel, Ramazan Gokberk Cinbis +2
In many real-world problems, there is typically a large discrepancy between the characteristics of data used in training versus deployment. A prime example is the analysis of aggre…
Image Captioning with Unseen Objects
Berkan Demirel, Ramazan Gokberk Cinbis, Nazli Ikizler-Cinbis
Image caption generation is a long standing and challenging problem at the intersection of computer vision and natural language processing. A number of recently proposed approaches…
Zero-Shot Sign Language Recognition: Can Textual Data Uncover Sign Languages?
Yunus Can Bilge, Nazli Ikizler-Cinbis, Ramazan Gokberk Cinbis
We introduce the problem of zero-shot sign language recognition (ZSSLR), where the goal is to leverage models learned over the seen sign class examples to recognize the instances o…
Learning Visually Consistent Label Embeddings for Zero-Shot Learning
Berkan Demirel, Ramazan Gokberk Cinbis, Nazli Ikizler-Cinbis
In this work, we propose a zero-shot learning method to effectively model knowledge transfer between classes via jointly learning visually consistent word vectors and label embeddi…
RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes
Semih Yagcioglu, Aykut Erdem, Erkut Erdem +1
Understanding and reasoning about cooking recipes is a fruitful research direction towards enabling machines to interpret procedural text. In this work, we introduce RecipeQA, a da…
Wildest Faces: Face Detection and Recognition in Violent Settings
Mehmet Kerim Yucel, Yunus Can Bilge, Oguzhan Oguz +3
With the introduction of large-scale datasets and deep learning models capable of learning complex representations, impressive advances have emerged in face detection and recogniti…
Zero-Shot Object Detection by Hybrid Region Embedding
Berkan Demirel, Ramazan Gokberk Cinbis, Nazli Ikizler-Cinbis
Object detection is considered as one of the most challenging problems in computer vision, since it requires correct prediction of both classes and locations of objects in images.…
Attributes2Classname: A discriminative model for attribute-based unsupervised zero-shot learning
Berkan Demirel, Ramazan Gokberk Cinbis, Nazli Ikizler-Cinbis
We propose a novel approach for unsupervised zero-shot learning (ZSL) of classes based on their names. Most existing unsupervised ZSL methods aim to learn a model for directly comp…
Re-evaluating Automatic Metrics for Image Captioning
Mert Kilickaya, Aykut Erdem, Nazli Ikizler-Cinbis +1
The task of generating natural language descriptions from images has received a lot of attention in recent years. Consequently, it is becoming increasingly important to evaluate su…
Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures
Raffaella Bernardi, Ruket Cakici, Desmond Elliott +6
Automatic description generation from natural images is a challenging problem that has recently received a large amount of interest from the computer vision and natural language pr…
Facial Descriptors for Human Interaction Recognition In Still Images
Gokhan Tanisik, Cemil Zalluhoglu, Nazli Ikizler-Cinbis
This paper presents a novel approach in a rarely studied area of computer vision: Human interaction recognition in still images. We explore whether the facial regions and their spa…