Min Shi
Orcid: 0000-0001-8209-9021Affiliations:
- Huazhong University of Science and Technology, School of Artificial Intelligence and Automation, Wuhan, China
According to our database1,
Min Shi
authored at least 16 papers
between 2021 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
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on orcid.org
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Bibliography
2025
NVDS$^{\mathbf{+}}$+: Towards Efficient and Versatile Neural Stabilizer for Video Depth Estimation.
IEEE Trans. Pattern Anal. Mach. Intell., January, 2025
2024
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024
The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Geometry-aware Reconstruction and Fusion-refined Rendering for Generalizable Neural Radiance Fields.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
2023
Proceedings of the 31st ACM International Conference on Multimedia, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
Phenotyping multiple maize ear traits from a single image: Kernels per ear, rows per ear, and kernels per row.
Comput. Electron. Agric., 2022
Design What You Desire: Icon Generation from Orthogonal Application and Theme Labels.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022
Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022
2021
Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report.
CoRR, 2021
Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops, 2021
Knowledge Distillation for Fast and Accurate Monocular Depth Estimation on Mobile Devices.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021