Articles with public access mandates - Hao SuLearn more
Not available anywhere: 2
Sofgan: A portrait image generator with dynamic styling
A Chen, R Liu, L Xie, Z Chen, H Su, J Yu
ACM Transactions on Graphics (TOG) 41 (1), 1-26, 2022
Mandates: Chinese Academy of Sciences, National Natural Science Foundation of China
Dictionary fields: Learning a neural basis decomposition
A Chen, Z Xu, X Wei, S Tang, H Su, A Geiger
ACM Transactions on Graphics (TOG) 42 (4), 1-12, 2023
Mandates: Swiss National Science Foundation
Available somewhere: 53
Pointnet: Deep learning on point sets for 3d classification and segmentation
H Su, CR Qi, K Mo, LJ Guibas
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Mandates: US National Science Foundation, US Department of Defense
Pointnet++: Deep hierarchical feature learning on point sets in a metric space
CR Qi, L Yi, H Su, LJ Guibas
Advances in neural information processing systems 30, 2017
Mandates: US National Science Foundation, US Department of Defense
Frustum pointnets for 3d object detection from rgb-d data
CR Qi, W Liu, C Wu, H Su, LJ Guibas
CVPR, 2018
Mandates: US National Science Foundation, US Department of Defense
A point set generation network for 3d object reconstruction from a single image
H Fan, H Su, LJ Guibas
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Mandates: US National Science Foundation
Volumetric and multi-view cnns for object classification on 3d data
H Su, CR Qi, M Nießner, A Dai, M Yan, LJ Guibas
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
Mandates: US National Science Foundation
A scalable active framework for region annotation in 3d shape collections
L Yi, VG Kim, D Ceylan, IC Shen, M Yan, H Su, C Lu, Q Huang, A Sheffer, ...
ACM Transactions on Graphics (ToG) 35 (6), 1-12, 2016
Mandates: US National Science Foundation, Natural Sciences and Engineering Research …
PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understanding
K Mo, S Zhu, AX Chang, L Yi, S Tripathi, LJ Guibas, H Su
CVPR 2019, 2018
Mandates: US National Science Foundation, US Department of Defense
Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo
A Chen, Z Xu, F Zhao, X Zhang, F Xiang, J Yu, H Su
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
Mandates: US National Science Foundation, National Natural Science Foundation of China
Syncspeccnn: Synchronized spectral cnn for 3d shape segmentation
L Yi, H Su, X Guo, LJ Guibas
Proceedings of the IEEE conference on computer vision and pattern …, 2017
Mandates: US National Science Foundation, US Department of Defense
Sapien: A simulated part-based interactive environment
F Xiang, Y Qin, K Mo, Y Xia, H Zhu, F Liu, M Liu, H Jiang, Y Yuan, H Wang, ...
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
Mandates: US National Science Foundation, US Department of Defense
Fpnn: Field probing neural networks for 3d data
Y Li, S Pirk, H Su, CR Qi, LJ Guibas
Advances in neural information processing systems 29, 2016
Mandates: US National Science Foundation
Learning shape abstractions by assembling volumetric primitives
S Tulsiani, H Su, LJ Guibas, AA Efros, J Malik
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
Mandates: US National Science Foundation
Point-based multi-view stereo network
R Chen, S Han, J Xu, H Su
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
Mandates: US National Science Foundation
Objectnet3d: A large scale database for 3d object recognition
Y Xiang, W Kim, W Chen, J Ji, C Choy, H Su, R Mottaghi, L Guibas, ...
Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016
Mandates: US National Science Foundation
Deep stereo using adaptive thin volume representation with uncertainty awareness
S Cheng, Z Xu, S Zhu, Z Li, LE Li, R Ramamoorthi, H Su
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
Mandates: US National Science Foundation
Gnerf: Gan-based neural radiance field without posed camera
Q Meng, A Chen, H Luo, M Wu, H Su, L Xu, X He, J Yu
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Mandates: National Natural Science Foundation of China
Geometry guided convolutional neural networks for self-supervised video representation learning
C Gan, B Gong, K Liu, H Su, LJ Guibas
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Mandates: US National Science Foundation
Stabilizing deep q-learning with convnets and vision transformers under data augmentation
N Hansen, H Su, X Wang
Advances in neural information processing systems 34, 3680-3693, 2021
Mandates: US National Science Foundation, US Department of Defense
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