8 papers
Learning View-Dependent Splatting Kernels
Huakeng Ding, Zhanpeng Liu, Fan Pei +2
We present a differentiable framework to automatically learn view-dependent 2D kernels in a splatting-based pipeline to improve reconstruction quality and representation efficiency…
Depth Peeling for High-Fidelity Gaussian-Enhanced Surfel Rendering
Keyang Ye, Hongzhi Wu, Kun Zhou
Novel view synthesis has been significantly advanced by NeRFs and 3D Gaussian Splatting (3DGS), which require ordering volumetric samples or primitives for correct color blending.…
Differentiable Adaptive 4D Structured Illumination for Joint Capture of Shape and Reflectance
Huakeng Ding, Yaowen Chen, Kun Zhou +1
We present a differentiable framework to adaptively compute 4D illumination conditions with respect to an object, for efficient, high-quality simultaneous acquisition of its shape…
Sparse-to-Complete: From Sparse Image Captures to Complete 3D Scenes
Yiyang Shen, Yin Yang, Kun Zhou +1
We introduce S2C-3D, a novel sparse-view 3D reconstruction framework for high-fidelity and complete scene reconstruction from as few as six to eight images. Our framework features…
Neural Enhancement of Analytical Appearance Models
Xuanzhe Shen, Xiaohe Ma, Kun Zhou +1
Traditional analytical reflectance models, while compact and interpretable, lack the capacity to accurately represent physical measurements. Recent neural models, which closely fit…
When Gaussian Meets Surfel: Ultra-fast High-fidelity Radiance Field Rendering
Keyang Ye, Tianjia Shao, Kun Zhou
We introduce Gaussian-enhanced Surfels (GESs), a bi-scale representation for radiance field rendering, wherein a set of 2D opaque surfels with view-dependent colors represent the c…