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Shuran Song
Shuran Song
Verified email at cs.columbia.edu - Homepage
Title
Cited by
Cited by
Year
3d shapenets: A deep representation for volumetric shapes
Z Wu, S Song, A Khosla, F Yu, L Zhang, X Tang, J Xiao
Proceedings of the IEEE conference on computer vision and pattern …, 2015
61052015
Shapenet: An information-rich 3d model repository
AX Chang, T Funkhouser, L Guibas, P Hanrahan, Q Huang, Z Li, ...
arXiv preprint arXiv:1512.03012, 2015
50372015
Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
F Yu, A Seff, Y Zhang, S Song, T Funkhouser, J Xiao
arXiv preprint arXiv:1506.03365, 2015
21192015
Sun rgb-d: A rgb-d scene understanding benchmark suite
S Song, SP Lichtenberg, J Xiao
Proceedings of the IEEE conference on computer vision and pattern …, 2015
19272015
Matterport3d: Learning from rgb-d data in indoor environments
A Chang, A Dai, T Funkhouser, M Halber, M Niessner, M Savva, S Song, ...
International Conference on 3D Vision (3DV), 2017
16392017
Semantic scene completion from a single depth image
S Song, F Yu, A Zeng, AX Chang, M Savva, T Funkhouser
Proceedings of the IEEE conference on computer vision and pattern …, 2017
12382017
3dmatch: Learning local geometric descriptors from rgb-d reconstructions
A Zeng, S Song, M Nießner, M Fisher, J Xiao, T Funkhouser
Proceedings of the IEEE conference on computer vision and pattern …, 2017
9492017
Deep sliding shapes for amodal 3d object detection in rgb-d images
S Song, J Xiao
Proceedings of the IEEE conference on computer vision and pattern …, 2016
8292016
Robotic pick-and-place of novel objects in clutter with multi-affordance grasping and cross-domain image matching
A Zeng, S Song, KT Yu, E Donlon, FR Hogan, M Bauza, D Ma, O Taylor, ...
The International Journal of Robotics Research 41 (7), 690-705, 2022
6882022
Normalized object coordinate space for category-level 6d object pose and size estimation
H Wang, S Sridhar, J Huang, J Valentin, S Song, LJ Guibas
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
6252019
Learning synergies between pushing and grasping with self-supervised deep reinforcement learning
A Zeng, S Song, S Welker, J Lee, A Rodriguez, T Funkhouser
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018
5792018
Sliding shapes for 3d object detection in depth images
S Song, J Xiao
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
5412014
Multi-view self-supervised deep learning for 6d pose estimation in the amazon picking challenge
A Zeng, KT Yu, S Song, D Suo, E Walker, A Rodriguez, J Xiao
2017 IEEE international conference on robotics and automation (ICRA), 1386-1383, 2017
5342017
TossingBot: Learning to Throw Arbitrary Objects with Residual Physics
A Zeng, S Song, J Lee, A Rodriguez, T Funkhouser
Robotics: Science and Systems (RSS), 2019
3722019
Tracking revisited using RGBD camera: Unified benchmark and baselines
S Song, J Xiao
Proceedings of the IEEE international conference on computer vision, 233-240, 2013
3482013
Physically-based rendering for indoor scene understanding using convolutional neural networks
Y Zhang, S Song, E Yumer, M Savva, JY Lee, H Jin, T Funkhouser
Proceedings of the IEEE conference on computer vision and pattern …, 2017
2982017
Panocontext: A whole-room 3d context model for panoramic scene understanding
Y Zhang, S Song, P Tan, J Xiao
Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014
2832014
Neural illumination: Lighting prediction for indoor environments
S Song, T Funkhouser
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019
2772019
Clear grasp: 3d shape estimation of transparent objects for manipulation
S Sajjan, M Moore, M Pan, G Nagaraja, J Lee, A Zeng, S Song
2020 IEEE international conference on robotics and automation (ICRA), 3634-3642, 2020
2002020
Grasping in the wild: Learning 6dof closed-loop grasping from low-cost demonstrations
S Song, A Zeng, J Lee, T Funkhouser
IEEE Robotics and Automation Letters 5 (3), 4978-4985, 2020
1992020
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