Felix Jńremo Lawin
Felix Jńremo Lawin
Verified email at liu.se
Title
Cited by
Cited by
Year
Deep projective 3D semantic segmentation
FJ Lawin, M Danelljan, P Tosteberg, G Bhat, FS Khan, M Felsberg
International Conference on Computer Analysis of Images and Patterns, 95-107, 2017
1252017
Density Adaptive Point Set Registration
FJ Lawin, M Danelljan, FS Khan, PE ForssÚn, M Felsberg
arXiv preprint arXiv:1804.01495, 2018
272018
Learning Fast and Robust Target Models for Video Object Segmentation
A Robinson, FJ Lawin, M Danelljan, FS Khan, M Felsberg
arXiv preprint arXiv:2003.00908, 2020
232020
Efficient multi-frequency phase unwrapping using kernel density estimation
FJ Lawin, PE ForssÚn, H OvrÚn
European Conference on Computer Vision, 170-185, 2016
222016
Learning what to learn for video object segmentation
G Bhat, FJ Lawin, M Danelljan, A Robinson, M Felsberg, L Van Gool, ...
European Conference on Computer Vision, 777-794, 2020
20*2020
The eighth visual object tracking VOT2020 challenge results
M Kristan, A Leonardis, J Matas, M Felsberg, R Pflugfelder, ...
European Conference on Computer Vision, 547-601, 2020
132020
Object-based spatial similarity for semi-supervised video object segmentation
B Wang, C Zheng, N Wang, S Wang, X Zhang, S Liu, S Gao, K Lu, ...
Conference on Computer Vision and Pattern Recognition Workshops, 2019
72019
Discriminative Online Learning for Fast Video Object Segmentation
A Robinson, FJ Lawin, M Danelljan, FS Khan, M Felsberg
arXiv preprint arXiv:1904.08630, 2019
22019
Discriminative learning and target attention for the 2019 davis challenge on video object segmentation
M Robinson, FJ Lawin, M Danelljan, M Felsberg
The 2019 DAVIS Challenge on Video Object Segmentation-CVPR Workshops, 2019
22019
Assessing Losses for Point Set Registration
ACM Tavares, FJ Lawin, PE ForssÚn
IEEE Robotics and Automation Letters 5 (2), 3360-3367, 2020
12020
Registration Loss Learning for Deep Probabilistic Point Set Registration
FJ Lawin, PE ForssÚn
arXiv preprint arXiv:2011.02229, 2020
2020
Depth Data Processing and 3D Reconstruction Using the Kinect v2
F Jńremo Lawin
2015
Supplemental Material for Paper: Efficient Multi-Frequency Phase Unwrapping using Kernel Density Estimation
FJ Lawin, PE ForssÚn, H OvrÚn
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Articles 1–13