Folgen
Ruibo Li
Ruibo Li
Bestätigte E-Mail-Adresse bei e.ntu.edu.sg
Titel
Zitiert von
Zitiert von
Jahr
Monocular relative depth perception with web stereo data supervision
K Xian, C Shen, Z Cao, H Lu, Y Xiao, R Li, Z Luo
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
2162018
Deep attention-based classification network for robust depth prediction
R Li, K Xian, C Shen, Z Cao, H Lu, L Hang
Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019
1182019
Hcrf-flow: Scene flow from point clouds with continuous high-order crfs and position-aware flow embedding
R Li, G Lin, T He, F Liu, C Shen
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
502021
Self-point-flow: Self-supervised scene flow estimation from point clouds with optimal transport and random walk
R Li, G Lin, L Xie
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
502021
Rigidflow: Self-supervised scene flow learning on point clouds by local rigidity prior
R Li, C Zhang, G Lin, Z Wang, C Shen
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
462022
Meta navigator: Search for a good adaptation policy for few-shot learning
C Zhang, H Ding, G Lin, R Li, C Wang, C Shen
Proceedings of the IEEE/CVF international conference on computer vision …, 2021
452021
Efficient few-shot object detection via knowledge inheritance
Z Yang, C Zhang, R Li, Y Xu, G Lin
IEEE Transactions on Image Processing 32, 321-334, 2022
282022
Weakly supervised segmentation on outdoor 4D point clouds with temporal matching and spatial graph propagation
H Shi, J Wei, R Li, F Liu, G Lin
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
272022
3d pose transfer with correspondence learning and mesh refinement
C Song, J Wei, R Li, F Liu, G Lin
Advances in Neural Information Processing Systems 34, 3108-3120, 2021
262021
Unsupervised 3d pose transfer with cross consistency and dual reconstruction
C Song, J Wei, R Li, F Liu, G Lin
IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (8), 10488 …, 2023
162023
3D reconstruction from non-uniform point clouds via local hierarchical clustering
J Yang, R Li, Y Xiao, Z Cao
Ninth International Conference on Digital Image Processing (ICDIP 2017 …, 2017
102017
Weakly supervised class-agnostic motion prediction for autonomous driving
R Li, H Shi, Z Fu, Z Wang, G Lin
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
82023
Label-guided knowledge distillation for continual semantic segmentation on 2d images and 3d point clouds
Z Yang, R Li, E Ling, C Zhang, Y Wang, D Huang, KT Ma, M Hur, G Lin
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
32023
Depth image super-resolution via semi self-taught learning framework
F Zhao, Z Cao, Y Xiao, X Zhang, K Xian, R Li
Videometrics, range imaging, and applications XIV 10332, 216-226, 2017
32017
RWSeg: Cross-graph Competing Random Walks for Weakly Supervised 3D Instance Segmentation
S Dong, R Li, J Wei, F Liu, G Lin
arXiv preprint arXiv:2208.05110, 2022
22022
Temporal Feature Matching and Propagation for Semantic Segmentation on 3D Point Cloud Sequences
H Shi, R Li, F Liu, G Lin
IEEE Transactions on Circuits and Systems for Video Technology 33 (12), 7491 …, 2023
12023
Collaborative propagation on multiple instance graphs for 3d instance segmentation with single-point supervision
S Dong, R Li, J Wei, F Liu, G Lin
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
12023
Self-Supervised 3D Scene Flow Estimation and Motion Prediction using Local Rigidity Prior
R Li, C Zhang, Z Wang, C Shen, G Lin
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024
2024
Motion estimation and prediction from 3D point clouds
R Li
Nanyang Technological University, 2024
2024
A novel sparse-to-dense depth map generation framework for monocular videos
R Zhang, Z Cao, Q Zhang, Y Xiao, R Li
Automated Visual Inspection and Machine Vision II 10334, 133-140, 2017
2017
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20