Articles with public access mandates - Or LitanyLearn more
Not available anywhere: 1
Fully Spectral Partial Shape Matching
O Litany, E Rodolà, AM Bronstein, MM Bronstein
Computer Graphics Forum 36 (2), 2017
Mandates: European Commission
Available somewhere: 22
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
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: US National Science Foundation
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
Mandates: European Commission
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
Mandates: US Department of Defense
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
Mandates: European Commission, Government of Italy
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
Mandates: European Commission
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
Mandates: Swiss National Science Foundation, European Commission
Mix3D: Out-of-Context Data Augmentation for 3D Scenes
A Nekrasov, J Schult, O Litany, B Leibe, F Engelmann
3DV 2021, 2021
Mandates: European Commission
3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection
H Wang, Y Cong, O Litany, Y Gao, LJ Guibas
CVPR 2021, 2020
Mandates: US National Science Foundation, US Department of Defense
Generating Useful Accident-Prone Driving Scenarios via a Learned Traffic Prior
D Rempe, J Philion, LJ Guibas, S Fidler, O Litany
CVPR 2022, 2021
Mandates: US Department of Defense
Weakly Supervised Learning of Rigid 3D Scene Flow
Z Gojcic, O Litany, A Wieser, LJ Guibas, T Birdal
CVPR 2021, 2021
Mandates: US National Science Foundation, US Department of Defense
Learning smooth neural functions via lipschitz regularization
HTD Liu, F Williams, A Jacobson, S Fidler, O Litany
ACM SIGGRAPH 2022 Conference Proceedings, 1-13, 2022
Mandates: Natural Sciences and Engineering Research Council of Canada
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
Mandates: European Commission
DIB-R++: Learning to Predict Lighting and Material with a Hybrid Differentiable Renderer
W Chen, J Litalien, J Gao, Z Wang, CF Tsang, S Khamis, O Litany, ...
NeurIPS 2021, 2021
Mandates: Natural Sciences and Engineering Research Council of Canada
Towards precise completion of deformable shapes
O Halimi, I Imanuel, O Litany, G Trappolini, E Rodolà, L Guibas, R Kimmel
Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020
Mandates: US Department of Defense, European Commission, Government of Italy
Shape correspondence with isometric and non-isometric deformations
RM Dyke, C Stride, YK Lai, PL Rosin, M Aubry, A Boyarski, AM Bronstein, ...
The Eurographics Association, 2019
Mandates: UK Engineering and Physical Sciences Research Council
Multi-track timeline control for text-driven 3d human motion generation
M Petrovich, O Litany, U Iqbal, MJ Black, G Varol, X Bin Peng, D Rempe
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
Mandates: Agence Nationale de la Recherche
Unscene3d: Unsupervised 3d instance segmentation for indoor scenes
D Rozenberszki, O Litany, A Dai
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
Mandates: European Commission
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