168 citations · 222 across the 12 of their papers we have counts for
13 papers
Knowledge Distillation Layer that Lets the Student Decide
Ada Gorgun, Yeti Z. Gurbuz, A. Aydin Alatan
Typical technique in knowledge distillation (KD) is regularizing the learning of a limited capacity model (student) by pushing its responses to match a powerful model's (teacher).…
Generalizable Embeddings with Cross-batch Metric Learning
Yeti Z. Gurbuz, A. Aydin Alatan
Global average pooling (GAP) is a popular component in deep metric learning (DML) for aggregating features. Its effectiveness is often attributed to treating each feature vector as…
MAEVI: Motion Aware Event-Based Video Frame Interpolation
Ahmet Akman, Onur Selim Kılıç, A. Aydın Alatan
Utilization of event-based cameras is expected to improve the visual quality of video frame interpolation solutions. We introduce a learning-based method to exploit moving region b…
Feature Embedding by Template Matching as a ResNet Block
Ada Gorgun, Yeti Z. Gurbuz, A. Aydin Alatan
Convolution blocks serve as local feature extractors and are the key to success of the neural networks. To make local semantic feature embedding rather explicit, we reformulate con…
E-VFIA : Event-Based Video Frame Interpolation with Attention
Onur Selim Kılıç, Ahmet Akman, A. Aydın Alatan
Video frame interpolation (VFI) is a fundamental vision task that aims to synthesize several frames between two consecutive original video images. Most algorithms aim to accomplish…
Effect of Parameter Optimization on Classical and Learning-based Image Matching Methods
Ufuk Efe, Kutalmis Gokalp Ince, A. Aydin Alatan
Deep learning-based image matching methods are improved significantly during the recent years. Although these methods are reported to outperform the classical techniques, the perfo…
Semi-Automatic Annotation For Visual Object Tracking
Kutalmis Gokalp Ince, Aybora Koksal, Arda Fazla +1
We propose a semi-automatic bounding box annotation method for visual object tracking by utilizing temporal information with a tracking-by-detection approach. For detection, we use…
Blind Deinterleaving of Signals in Time Series with Self-attention Based Soft Min-cost Flow Learning
Oğul Can, Yeti Z. Gürbüz, Berkin Yıldırım +1
We propose an end-to-end learning approach to address deinterleaving of patterns in time series, in particular, radar signals. We link signal clustering problem to min-cost flow as…
Effect of Annotation Errors on Drone Detection with YOLOv3
Aybora Koksal, Kutalmis Gokalp Ince, A. Aydin Alatan
Following the recent advances in deep networks, object detection and tracking algorithms with deep learning backbones have been improved significantly; however, this rapid developm…
Quadruplet Selection Methods for Deep Embedding Learning
Kaan Karaman, Erhan Gundogdu, Aykut Koc +1
Recognition of objects with subtle differences has been used in many practical applications, such as car model recognition and maritime vessel identification. For discrimination of…
Deep Metric Learning with Alternating Projections onto Feasible Sets
Oğul Can, Yeti Ziya Gürbüz, A. Aydın Alatan
During the training of networks for distance metric learning, minimizers of the typical loss functions can be considered as "feasible points" satisfying a set of constraints impose…
Good Features to Correlate for Visual Tracking
Erhan Gundogdu, A. Aydin Alatan
During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in these family of…
Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters
Ozan Sener, Kemal Ugur, A. Aydin Alatan
Segmentation of an object from a video is a challenging task in multimedia applications. Depending on the application, automatic or interactive methods are desired; however, regard…