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Or Litany
Or Litany
Research Scientist, NVIDIA
Verified email at nvidia.com - Homepage
Title
Cited by
Cited by
Year
Deep Hough Voting for 3D Object Detection in Point Clouds
CR Qi, O Litany, K He, LJ Guibas
ICCV 2019 (Oral, Best Paper Nomination), 2019
5322019
Deformable shape completion with graph convolutional autoencoders
O Litany, A Bronstein, M Bronstein, A Makadia
Proceedings of the IEEE conference on computer vision and pattern …, 2018
1832018
Deep functional maps: Structured prediction for dense shape correspondence
O Litany, T Remez, E Rodola, A Bronstein, M Bronstein
Proceedings of the IEEE international conference on computer vision, 5659-5667, 2017
1792017
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
S Xie, J Gu, D Guo, CR Qi, LJ Guibas, O Litany
ECCV 2020 Spotlight, 2020
1392020
ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes
CR Qi, X Chen, O Litany, LJ Guibas
CVPR 2020, 2020
1282020
Class-aware fully convolutional Gaussian and Poisson denoising
T Remez, O Litany, R Giryes, AM Bronstein
IEEE Transactions on Image Processing 27 (11), 5707-5722, 2018
111*2018
Fully Spectral Partial Shape Matching
O Litany, E Rodolà, AM Bronstein, MM Bronstein
Computer Graphics Forum 36 (2), 2017
932017
Unsupervised learning of dense shape correspondence
O Halimi, O Litany, E Rodola, AM Bronstein, R Kimmel
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
90*2019
Non-Rigid Puzzles
O Litany, E Rodolà, AM Bronstein, MM Bronstein, D Cremers
Computer Graphics Forum 35 (5), 135-143 (Best paper award at SGP), 2016
772016
Efficient deformable shape correspondence via kernel matching
Z Lähner, M Vestner, A Boyarski, O Litany, R Slossberg, T Remez, ...
3DV, 2017
72*2017
Deep class-aware image denoising
T Remez, O Litany, R Giryes, AM Bronstein
2017 international conference on sampling theory and applications (SampTA …, 2017
602017
On Learning Sets of Symmetric Elements
H Maron, O Litany, G Chechik, E Fetaya
ICML 2020 -- Outstanding paper award, 2020
552020
Dual-primal graph convolutional networks
F Monti, O Shchur, A Bojchevski, O Litany, S Günnemann, MM Bronstein
arXiv preprint arXiv:1806.00770, 2018
392018
Weakly Supervised Learning of Rigid 3D Scene Flow
Z Gojcic, O Litany, A Wieser, LJ Guibas, T Birdal
CVPR 2021, 2021
272021
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection
H Wang, Y Cong, O Litany, Y Gao, LJ Guibas
CVPR 2021, 2020
262020
SHREC'17: Deformable shape retrieval with missing parts
E Rodolà, L Cosmo, O Litany, MM Bronstein, AM Bronstein, N Audebert, ...
10th Eurographics Workshop on 3D Object Retrieval, 3DOR 2017, 85-94, 2017
262017
ReLMoGen: Integrating motion generation in reinforcement learning for mobile manipulation
F Xia, C Li, R Martín-Martín, O Litany, A Toshev, S Savarese
2021 IEEE International Conference on Robotics and Automation (ICRA), 4583-4590, 2021
22*2021
A picture is worth a billion bits: Real-time image reconstruction from dense binary threshold pixels
T Remez, O Litany, A Bronstein
2016 IEEE International Conference on Computational Photography (ICCP), 1-9, 2016
21*2016
Mix3D: Out-of-Context Data Augmentation for 3D Scenes
A Nekrasov, J Schult, O Litany, B Leibe, F Engelmann
3DV 2021, 2021
152021
Continuous Geodesic Convolutions for Learning on 3D Shapes
Z Yang, O Litany, T Birdal, S Sridhar, L Guibas
WACV 2021, 2020
152020
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