Search Results for author: Caglar Aytekin

Found 11 papers, 0 papers with code

A Compression Objective and a Cycle Loss for Neural Image Compression

no code implementations24 May 2019 Caglar Aytekin, Francesco Cricri, Antti Hallapuro, Jani Lainema, Emre Aksu, Miska Hannuksela

In this manuscript we propose two objective terms for neural image compression: a compression objective and a cycle loss.

Image Compression MS-SSIM +1

Compressing Weight-updates for Image Artifacts Removal Neural Networks

no code implementations10 May 2019 Yat Hong Lam, Alireza Zare, Caglar Aytekin, Francesco Cricri, Jani Lainema, Emre Aksu, Miska Hannuksela

In this paper, we present a novel approach for fine-tuning a decoder-side neural network in the context of image compression, such that the weight-updates are better compressible.

Fine-tuning Image Compression +1

Compressibility Loss for Neural Network Weights

no code implementations3 May 2019 Caglar Aytekin, Francesco Cricri, Emre Aksu

In this paper we apply a compressibility loss that enables learning highly compressible neural network weights.

Saliency-Enhanced Robust Visual Tracking

no code implementations8 Feb 2018 Caglar Aytekin, Francesco Cricri, Emre Aksu

In this work, we propose an improvement over DCF based trackers by combining saliency based and other features based filter responses.

RGB Salient Object Detection Salient Object Detection +2

A Theoretical Investigation of Graph Degree as an Unsupervised Normality Measure

no code implementations24 Jan 2018 Caglar Aytekin, Francesco Cricri, Lixin Fan, Emre Aksu

In order to have an in-depth theoretical understanding, in this manuscript, we investigate the graph degree in spectral graph clustering based and kernel based point of views and draw connections to a recent kernel method for the two sample problem.

Graph Clustering Spectral Graph Clustering +1

Memory-Efficient Deep Salient Object Segmentation Networks on Gridized Superpixels

no code implementations27 Dec 2017 Caglar Aytekin, Xingyang Ni, Francesco Cricri, Lixin Fan, Emre Aksu

By using these encoded images, we train a memory-efficient network using only 0. 048\% of the number of parameters that other deep salient object detection networks have.

RGB Salient Object Detection Salient Object Detection +2

INTEL-TUT Dataset for Camera Invariant Color Constancy Research

no code implementations21 Mar 2017 Caglar Aytekin, Jarno Nikkanen, Moncef Gabbouj

In this paper, we provide a novel dataset designed for camera invariant color constancy research.

Color Constancy

Probabilistic Saliency Estimation

no code implementations13 Sep 2016 Caglar Aytekin, Alexandros Iosifidis, Moncef Gabbouj

In this paper, we model the salient object detection problem under a probabilistic framework encoding the boundary connectivity saliency cue and smoothness constraints in an optimization problem.

RGB Salient Object Detection Saliency Prediction +1

Cannot find the paper you are looking for? You can Submit a new open access paper.