Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Andreas Aakerberg"'
Publikováno v:
IET Image Processing, Vol 16, Iss 2, Pp 442-452 (2022)
Abstract Most existing face image Super‐Resolution (SR) methods assume that the Low‐Resolution (LR) images were artificially downsampled from High‐Resolution (HR) images with bicubic interpolation. This operation changes the natural image chara
Externí odkaz:
https://doaj.org/article/430c3c3cdb284ee1a679b242c6c2af8e
Publikováno v:
Image Analysis ISBN: 9783031314346
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a4d28ab29dc2123fea4b604931580199
https://doi.org/10.1007/978-3-031-31435-3_11
https://doi.org/10.1007/978-3-031-31435-3_11
Publikováno v:
Aakerberg, A, Johansen, A S, Nasrollahi, K & Moeslund, T B 2022, Semantic Segmentation Guided Real-World Super-Resolution . in Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, 2022 ., 9707555, IEEE, IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), 2022 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW), Waikoloa, Hawaii, United States, 04/01/2022 . https://doi.org/10.1109/WACVW54805.2022.00051
Real-world single image Super-Resolution (SR) aims toenhance the resolution and reconstruct High-Resolution(HR) details of real Low-Resolution (LR) images. This isdifferent from the traditional SR setting, where the LR im-ages are synthetically creat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aaa97073388ce9d317e092af04430685
https://doi.org/10.1109/wacvw54805.2022.00051
https://doi.org/10.1109/wacvw54805.2022.00051
Publikováno v:
Aakerberg, A, Johansen, A S, Nasrollahi, K & Moeslund, T B 2021, Single-Loss Multi-task Learning For Improving Semantic Segmentation Using Super-Resolution . in N Tsapatsoulis, A Panayides, T Theocharides, A Lanitis, A Lanitis, C Pattichis, C Pattichis & M Vento (eds), Computer Analysis of Images and Patterns-19th International Conference, CAIP 2021, Proceedings . vol. 13053, Springer Science+Business Media, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13053 LNCS, pp. 403-411, 19th International Conference on Computer Analysis of Images and Patterns, CAIP 2021, Virtual, Online, 28/09/2021 . https://doi.org/10.1007/978-3-030-89131-2_37
Aalborg University
Computer Analysis of Images and Patterns ISBN: 9783030891305
CAIP (2)
Aalborg University
Computer Analysis of Images and Patterns ISBN: 9783030891305
CAIP (2)
We propose a novel means to improve the accuracy of semantic segmentation based on multi-task learning. More specifically, in our Multi-Task Semantic Segmentation and Super-Resolution (MT-SSSR) framework, we jointly train a super-resolution and seman
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad88e09a0e080fe22d0f0171f21be8c3
https://vbn.aau.dk/da/publications/b8149acd-ae34-466e-9bdf-502215eafa5f
https://vbn.aau.dk/da/publications/b8149acd-ae34-466e-9bdf-502215eafa5f
Publikováno v:
IPTA
Aakerberg, A, Nasrollahi, K & Heder, T 2018, Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning . in 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA) ., 8310101, IEEE, International Conference on Image Processing Theory, Tools and Applications (IPTA), pp. 1-6, International Conference on Image Processing Theory, Tools and Applications, Montreal, Canada, 28/11/2017 . https://doi.org/10.1109/IPTA.2017.8310101, https://doi.org/10.1109/IPTA.2017.8310101
Aakerberg, A, Nasrollahi, K & Heder, T 2018, Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning . in 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA) ., 8310101, IEEE, International Conference on Image Processing Theory, Tools and Applications (IPTA), pp. 1-6, International Conference on Image Processing Theory, Tools and Applications, Montreal, Canada, 28/11/2017 . https://doi.org/10.1109/IPTA.2017.8310101, https://doi.org/10.1109/IPTA.2017.8310101
Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::02b869a6ecb925f84ee904b766372ddd
https://doi.org/10.1109/ipta.2017.8310101
https://doi.org/10.1109/ipta.2017.8310101
Publikováno v:
Video Analytics. Face and Facial Expression Recognition and Audience Measurement ISBN: 9783319566863
Super-resolution algorithms are used to improve the quality and resolution of low-resolution images. These algorithms can be divided into two classes of hallucination- and reconstruction-based ones. The improvement factors of these algorithms are lim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::317276523277287edadc34b88ad99155
https://doi.org/10.1007/978-3-319-56687-0_11
https://doi.org/10.1007/978-3-319-56687-0_11
Publikováno v:
Aalborg University
Aakerberg, A, Nasrollahi, K & Moeslund, T B 2021, RELLISUR: A Real Low-Light Image Super-Resolution Dataset . in Advances in Neural Information Processing Systems 35 (NeurIPS 2021) . Thirty-fifth Conference on Neural Information Processing Systems-NeurIPS 2021, 06/12/2021 .
Aakerberg, A, Nasrollahi, K & Moeslund, T B 2021, RELLISUR: A Real Low-Light Image Super-Resolution Dataset . in Advances in Neural Information Processing Systems 35 (NeurIPS 2021) . Thirty-fifth Conference on Neural Information Processing Systems-NeurIPS 2021, 06/12/2021 .
In this paper, we introduce RELLISUR, a novel dataset of real low-light low-resolution images paired with normal-light high-resolution reference image counterparts. With this dataset, we seek to fill the gap between low-light image enhancement and lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::0454e1c02af6ea704b0925dce20df0cd
https://vbn.aau.dk/en/publications/65c83732-4bb9-4aee-8bf7-eb58026a0e68
https://vbn.aau.dk/en/publications/65c83732-4bb9-4aee-8bf7-eb58026a0e68