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Kin-Chung Chan

4 papers

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papers

Publications (4)

cs.CV2025

See In Detail: Enhancing Sparse-view 3D Gaussian Splatting with Local Depth and Semantic Regularization

Zongqi He, Zhe Xiao, Kin-Chung Chan +3

3D Gaussian Splatting (3DGS) has shown remarkable performance in novel view synthesis. However, its rendering quality deteriorates with sparse inphut views, leading to distorted co…

cs.CV2024

AIM 2024 Sparse Neural Rendering Challenge: Methods and Results

Michal Nazarczuk, Sibi Catley-Chandar, Thomas Tanay +27

This paper reviews the challenge on Sparse Neural Rendering that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2024. This manuscript…

cs.CV2025

Enhancing Novel View Synthesis from extremely sparse views with SfM-free 3D Gaussian Splatting Framework

Zongqi He, Hanmin Li, Kin-Chung Chan +5

3D Gaussian Splatting (3DGS) has demonstrated remarkable real-time performance in novel view synthesis, yet its effectiveness relies heavily on dense multi-view inputs with precise…

cs.CV2024

Towards Multi-View Consistent Style Transfer with One-Step Diffusion via Vision Conditioning

Yushen Zuo, Jun Xiao, Kin-Chung Chan +5

The stylization of 3D scenes is an increasingly attractive topic in 3D vision. Although image style transfer has been extensively researched with promising results, directly applyi…

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