Shuwei Shao

Orcid: 0000-0001-8057-1599

According to our database1, Shuwei Shao authored at least 16 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
Sparse Pseudo-LiDAR Depth Assisted Monocular Depth Estimation.
IEEE Trans. Intell. Veh., January, 2024

URCDC-Depth: Uncertainty Rectified Cross-Distillation With CutFlip for Monocular Depth Estimation.
IEEE Trans. Multim., 2024

F<sup>2</sup>Depth: Self-supervised Indoor Monocular Depth Estimation via Optical Flow Consistency and Feature Map Synthesis.
CoRR, 2024

2023
Self-Supervised Monocular Depth Estimation With Self-Reference Distillation and Disparity Offset Refinement.
IEEE Trans. Circuits Syst. Video Technol., December, 2023

Towards Comprehensive Monocular Depth Estimation: Multiple Heads are Better Than One.
IEEE Trans. Multim., 2023

A geometry-aware deep network for depth estimation in monocular endoscopy.
Eng. Appl. Artif. Intell., 2023

MonoDiffusion: Self-Supervised Monocular Depth Estimation Using Diffusion Model.
CoRR, 2023

NDDepth: Normal-Distance Assisted Monocular Depth Estimation and Completion.
CoRR, 2023

IEBins: Iterative Elastic Bins for Monocular Depth Estimation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Monocular Depth Estimation: A Survey.
Proceedings of the 49th Annual Conference of the IEEE Industrial Electronics Society, 2023

NDDepth: Normal-Distance Assisted Monocular Depth Estimation.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Self-Supervised monocular depth and ego-Motion estimation in endoscopy: Appearance flow to the rescue.
Medical Image Anal., 2022

SMUDLP: Self-Teaching Multi-Frame Unsupervised Endoscopic Depth Estimation with Learnable Patchmatch.
CoRR, 2022

A multi-scale unsupervised learning for deformable image registration.
Int. J. Comput. Assist. Radiol. Surg., 2022

2021
NENet: Monocular Depth Estimation via Neural Ensembles.
CoRR, 2021

Self-Supervised Learning for Monocular Depth Estimation on Minimally Invasive Surgery Scenes.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021


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