Gabriel Eilertsen
Title
Cited by
Cited by
Year
HDR image reconstruction from a single exposure using deep CNNs
G Eilertsen, J Kronander, G Denes, RK Mantiuk, J Unger
ACM transactions on graphics (TOG) 36 (6), 1-15, 2017
2742017
Evaluation of tone mapping operators for HDR-video
G Eilertsen, R Wanat, J Unger, RK Mantiuk
Computer Graphics Forum (Proceedings of Pacific Graphics 2013) 32 (7), 275-284, 2013
1282013
A comparative review of tone-mapping algorithms for high dynamic range video
G Eilertsen, RK Mantiuk, J Unger
Computer Graphics Forum (Proceedings of Eurographics 2017) 36 (2), 2017
782017
Real-time noise-aware tone mapping
G Eilertsen, RK Mantiuk, J Unger
ACM Transactions on Graphics (TOG) 34 (6), 2015
662015
A closer look at domain shift for deep learning in histopathology
K Stacke, G Eilertsen, J Unger, C Lundström
arXiv preprint arXiv:1909.11575, 2019
242019
Survey and evaluation of tone mapping operators for HDR video
G Eilertsen, J Unger, R Wanat, R Mantiuk
ACM SIGGRAPH 2013 Talks, 1-1, 2013
222013
Single-frame regularization for temporally stable cnns
G Eilertsen, RK Mantiuk, J Unger
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
142019
A high dynamic range video codec optimized by large-scale testing
G Eilertsen, RK Mantiuk, J Unger
IEEE International Conference on Image Processing (ICIP), 1379-1383, 2016
112016
Measuring domain shift for deep learning in histopathology
K Stacke, G Eilertsen, J Unger, C Lundström
IEEE journal of biomedical and health informatics 25 (2), 325-336, 2020
102020
A survey of image synthesis methods for visual machine learning
A Tsirikoglou, G Eilertsen, J Unger
Computer Graphics Forum 39 (6), 426-451, 2020
102020
Survey of XAI in digital pathology
M Pocevičiūtė, G Eilertsen, C Lundström
Artificial Intelligence and Machine Learning for Digital Pathology, 56-88, 2020
82020
BriefMatch: Dense binary feature matching for real-time optical flow estimation
G Eilertsen, PE Forssén, J Unger
Scandinavian Conference on Image Analysis (SCIA17), 2017
82017
Classifying the classifier: dissecting the weight space of neural networks
G Eilertsen, D Jönsson, T Ropinski, J Unger, A Ynnerman
European Conference on Artificial Intelligence 325, 1119-1126, 2020
62020
The high dynamic range imaging pipeline: Tone-mapping, distribution, and single-exposure reconstruction
G Eilertsen
Linköping University Electronic Press, 2018
62018
A versatile material reflectance measurement system for use in production
G Eilertsen, P Larsson, J Unger
SIGRAD, 69-76, 2011
62011
Perceptually based parameter adjustments for video processing operations
G Eilertsen, J Unger, R Wanat, R Mantiuk
ACM SIGGRAPH 2014 Talks, 1-1, 2014
32014
A study of deep learning colon cancer detection in limited data access scenarios
A Tsirikoglou, K Stacke, G Eilertsen, M Lindvall, J Unger
arXiv preprint arXiv:2005.10326, 2020
22020
The HDR-video pipeline: From capture and image reconstruction to compression and tone mapping
J Unger, F Banterle, R Mantiuk, G Eilertsen
Eurographics 2016, May 9, Lisbon, Portugal, 1-6, 2016
2*2016
Luma HDRv: an open source high dynamic range video codec optimized by large-scale testing
G Eilertsen, RK Mantiuk, J Unger
ACM SIGGRAPH 2016 Talks, 17, 2016
22016
Unsupervised anomaly detection in digital pathology using GANs
M Pocevičiūtė, G Eilertsen, C Lundström
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1878-1882, 2021
12021
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