Zhihao Liang

Orcid: 0009-0000-2195-7918

Affiliations:
  • South China University of Technology, School of Electronic and Information Engineering, Guangzhou, China
  • DexForce Technology Co., Ltd


According to our database1, Zhihao Liang authored at least 13 papers between 2021 and 2025.

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

2025
GUS-IR: Gaussian Splatting With Unified Shading for Inverse Rendering.
IEEE Trans. Pattern Anal. Mach. Intell., October, 2025

ARMesh: Autoregressive Mesh Generation via Next-Level-of-Detail Prediction.
CoRR, September, 2025

IR-Pro: Baking Probes to Model Indirect Illumination for Inverse Rendering of Scenes.
IEEE Signal Process. Lett., 2025

2024
Exploring Diversity-Based Active Learning for 3D Object Detection in Autonomous Driving.
IEEE Trans. Intell. Transp. Syst., November, 2024

Advances in 3D Generation: A Survey.
CoRR, 2024

Sur2f: A Hybrid Representation for High-Quality and Efficient Surface Reconstruction from Multi-view Images.
CoRR, 2024

Analytic-Splatting: Anti-Aliased 3D Gaussian Splatting via Analytic Integration.
Proceedings of the Computer Vision - ECCV 2024, 2024

Sur<sup>2</sup>f: A Hybrid Representation for High-Quality and Efficient Surface Reconstruction from Multi-view Images.
Proceedings of the Computer Vision - ECCV 2024, 2024

GS-IR: 3D Gaussian Splatting for Inverse Rendering.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
HelixSurf: A Robust and Efficient Neural Implicit Surface Learning of Indoor Scenes with Iterative Intertwined Regularization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Exploring Diversity-based Active Learning for 3D Object Detection in Autonomous Driving.
CoRR, 2022

VISTA: Boosting 3D Object Detection via Dual Cross-VIew SpaTial Attention.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021


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