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2020 – today
- 2023
[c7]Rohith Agaram, Shaurya Dewan, Rahul Sajnani, Adrien Poulenard, K. Madhava Krishna, Srinath Sridhar:
Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields. CVPR 2023: 4500-4510- [c6]Qiuhong Anna Wei, Sijie Ding, Jeong Joon Park
, Rahul Sajnani, Adrien Poulenard, Srinath Sridhar, Leonidas J. Guibas:
LEGO-Net: Learning Regular Rearrangements of Objects in Rooms. CVPR 2023: 19037-19047 - [i9]Qiuhong Anna Wei, Sijie Ding, Jeong Joon Park, Rahul Sajnani, Adrien Poulenard, Srinath Sridhar, Leonidas J. Guibas:
LEGO-Net: Learning Regular Rearrangements of Objects in Rooms. CoRR abs/2301.09629 (2023) - 2022
- [c5]Rahul Sajnani, Adrien Poulenard, Jivitesh Jain, Radhika Dua, Leonidas J. Guibas, Srinath Sridhar:
ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes. CVPR 2022: 16948-16958 - [i8]Rahul Sajnani, Adrien Poulenard, Jivitesh Jain, Radhika Dua, Leonidas J. Guibas, Srinath Sridhar:
ConDor: Self-Supervised Canonicalization of 3D Pose for Partial Shapes. CoRR abs/2201.07788 (2022) - [i7]Sidhika Balachandar, Adrien Poulenard, Congyue Deng, Leonidas J. Guibas:
Breaking the Symmetry: Resolving Symmetry Ambiguities in Equivariant Neural Networks. CoRR abs/2210.16646 (2022) - [i6]Adrien Poulenard, Maks Ovsjanikov, Leonidas J. Guibas:
Equivalence Between SE(3) Equivariant Networks via Steerable Kernels and Group Convolution. CoRR abs/2211.15903 (2022) - [i5]Rohith Agaram, Shaurya Dewan, Rahul Sajnani, Adrien Poulenard, K. Madhava Krishna, Srinath Sridhar:
Canonical Fields: Self-Supervised Learning of Pose-Canonicalized Neural Fields. CoRR abs/2212.02493 (2022) - 2021
- [c4]Adrien Poulenard, Leonidas J. Guibas:
A Functional Approach to Rotation Equivariant Non-Linearities for Tensor Field Networks. CVPR 2021: 13174-13183 - [c3]Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacchi, Leonidas J. Guibas:
Vector Neurons: A General Framework for SO(3)-Equivariant Networks. ICCV 2021: 12180-12189 - [i4]Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacchi, Leonidas J. Guibas:
Vector Neurons: A General Framework for SO(3)-Equivariant Networks. CoRR abs/2104.12229 (2021) - 2020
- [b1]Adrien Poulenard:
Structures for deep learning and topology optimization of functions on 3D shapes. (Structures pour l'apprentissage profond et l'optimisation de la topologie de fonctions sur les formes 3D). Institut Polytechnique de Paris, France, 2020
2010 – 2019
- 2019
- [c2]Adrien Poulenard, Marie-Julie Rakotosaona, Yann Ponty, Maks Ovsjanikov:
Effective Rotation-Invariant Point CNN with Spherical Harmonics Kernels. 3DV 2019: 47-56 - [c1]Simone Melzi, Riccardo Marin, Emanuele Rodolà, Umberto Castellani, Jing Ren, Adrien Poulenard, Peter Wonka, Maks Ovsjanikov:
Matching Humans with Different Connectivity. 3DOR@Eurographics 2019: 121-128 - [i3]Adrien Poulenard, Marie-Julie Rakotosaona, Yann Ponty, Maks Ovsjanikov:
Effective Rotation-invariant Point CNN with Spherical Harmonics kernels. CoRR abs/1906.11555 (2019) - 2018
- [j4]Adrien Poulenard, Primoz Skraba, Maks Ovsjanikov:
Topological Function Optimization for Continuous Shape Matching. Comput. Graph. Forum 37(5): 13-25 (2018) - [j3]Adrien Poulenard, Maks Ovsjanikov:
Multi-directional geodesic neural networks via equivariant convolution. ACM Trans. Graph. 37(6): 236 (2018) - [j2]Jing Ren, Adrien Poulenard, Peter Wonka, Maks Ovsjanikov:
Continuous and orientation-preserving correspondences via functional maps. ACM Trans. Graph. 37(6): 248 (2018) - [i2]Jing Ren, Adrien Poulenard, Peter Wonka, Maks Ovsjanikov:
Continuous and Orientation-preserving Correspondences via Functional Maps. CoRR abs/1806.04455 (2018) - [i1]Adrien Poulenard, Maks Ovsjanikov:
Multi-directional Geodesic Neural Networks via Equivariant Convolution. CoRR abs/1810.02303 (2018) - 2017
- [j1]Michaël Clément, Adrien Poulenard, Camille Kurtz, Laurent Wendling:
Directional Enlacement Histograms for the Description of Complex Spatial Configurations between Objects. IEEE Trans. Pattern Anal. Mach. Intell. 39(12): 2366-2380 (2017)
Coauthor Index
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