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Or Litany
Or Litany
Technion, NVIDIA
Dirección de correo verificada de nvidia.com - Página principal
Título
Citado por
Citado por
Año
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
13802019
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
6182020
Get3d: A generative model of high quality 3d textured shapes learned from images
J Gao, T Shen, Z Wang, W Chen, K Yin, D Li, O Litany, Z Gojcic, S Fidler
Advances In Neural Information Processing Systems 35, 31841-31854, 2022
3842022
Lion: Latent point diffusion models for 3d shape generation
A Vahdat, F Williams, Z Gojcic, O Litany, S Fidler, K Kreis
Advances in Neural Information Processing Systems 35, 10021-10039, 2022
3682022
Neural fields in visual computing and beyond
Y Xie, T Takikawa, S Saito, O Litany, S Yan, N Khan, F Tombari, ...
Computer Graphics Forum 41 (2), 641-676, 2022
3492022
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
3132017
ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes
CR Qi, X Chen, O Litany, LJ Guibas
CVPR 2020, 2020
3112020
Vector Neurons: A General Framework for SO (3)-Equivariant Networks
C Deng, O Litany, Y Duan, A Poulenard, A Tagliasacchi, L Guibas
ICCV 2021, 2021
2792021
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
2672018
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
1822019
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
169*2018
Mix3D: Out-of-Context Data Augmentation for 3D Scenes
A Nekrasov, J Schult, O Litany, B Leibe, F Engelmann
3DV 2021, 2021
1452021
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection
H Wang, Y Cong, O Litany, Y Gao, LJ Guibas
CVPR 2021, 2020
1312020
Language-Grounded Indoor 3D Semantic Segmentation in the Wild
D Rozenberszki, O Litany, A Dai
ECCV 2022, 2022
1292022
Fully Spectral Partial Shape Matching
O Litany, E Rodolà, AM Bronstein, MM Bronstein
Computer Graphics Forum 36 (2), 2017
1242017
On Learning Sets of Symmetric Elements
H Maron, O Litany, G Chechik, E Fetaya
ICML 2020 -- Outstanding paper award, 2020
1222020
Mask3d: Mask transformer for 3d semantic instance segmentation
J Schult, F Engelmann, A Hermans, O Litany, S Tang, B Leibe
2023 IEEE International Conference on Robotics and Automation (ICRA), 8216-8223, 2023
1172023
Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior
D Rempe, J Philion, LJ Guibas, S Fidler, O Litany
CVPR 2022, 2021
1092021
Weakly Supervised Learning of Rigid 3D Scene Flow
Z Gojcic, O Litany, A Wieser, LJ Guibas, T Birdal
CVPR 2021, 2021
1052021
Efficient deformable shape correspondence via kernel matching
Z Lähner, M Vestner, A Boyarski, O Litany, R Slossberg, T Remez, ...
3DV, 2017
104*2017
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