Shuwei Shao

Orcid: 0000-0001-8057-1599

According to our database1, Shuwei Shao authored at least 18 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • 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

F2Depth: Self-supervised indoor monocular depth estimation via optical flow consistency and feature map synthesis.
Eng. Appl. Artif. Intell., 2024

Digging into contrastive learning for robust depth estimation with diffusion models.
CoRR, 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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