Guangchi Fang

According to our database, Guangchi Fang authored at least 10 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Efficient Scene Modeling via Structure-Aware and Region-Prioritized 3D Gaussians.

Guangchi Fang, Bing Wang

IEEE Trans. Pattern Anal. Mach. Intell., April, 2026

PocketGS: On-Device Training of 3D Gaussian Splatting for High Perceptual Modeling.

Wenzhi Guo, Guangchi Fang, Shu Yang, Bing Wang

CoRR, January, 2026

2024

Mini-Splatting2: Building 360 Scenes within Minutes via Aggressive Gaussian Densification.

Guangchi Fang, Bing Wang

CoRR, 2024

ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression.

Guangchi Fang, Qingyong Hu, Longguang Wang, Yulan Guo

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Mini-Splatting: Representing Scenes with a Constrained Number of Gaussians.

Guangchi Fang, Bing Wang

Proceedings of the Computer Vision - ECCV 2024, 2024

2022

3DPointCaps++: Learning 3D Representations with Capsule Networks.

Yongheng Zhao, Guangchi Fang, Yulan Guo, Leonidas J. Guibas, Federico Tombari, Tolga Birdal

Int. J. Comput. Vis., 2022

4DAC: Learning Attribute Compression for Dynamic Point Clouds.

Guangchi Fang, Qingyong Hu, Yiling Xu, Yulan Guo

CoRR, 2022

SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds.

Qingyong Hu, Bo Yang, Guangchi Fang, Yulan Guo, Ales Leonardis, Niki Trigoni, Andrew Markham

Proceedings of the Computer Vision - ECCV 2022, 2022

3DAC: Learning Attribute Compression for Point Clouds.

Guangchi Fang, Qingyong Hu, Hanyun Wang, Yiling Xu, Yulan Guo

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

SQN: Weakly-Supervised Semantic Segmentation of Large-Scale 3D Point Clouds with 1000x Fewer Labels.

Qingyong Hu, Bo Yang, Guangchi Fang, Yulan Guo, Ales Leonardis, Niki Trigoni, Andrew Markham

CoRR, 2021