23 citations · 27 across the 9 of their papers we have counts for
9 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…
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…
MaterialPicker: Multi-Modal DiT-Based Material Generation
Xiaohe Ma, Valentin Deschaintre, Miloš Hašan +4
High-quality material generation is key for virtual environment authoring and inverse rendering. We propose MaterialPicker, a multi-modal material generator leveraging a Diffusion…
ARM: Appearance Reconstruction Model for Relightable 3D Generation
Xiang Feng, Chang Yu, Zoubin Bi +6
Recent image-to-3D reconstruction models have greatly advanced geometry generation, but they still struggle to faithfully generate realistic appearance. To address this, we introdu…
GS^3: Efficient Relighting with Triple Gaussian Splatting
Zoubin Bi, Yixin Zeng, Chong Zeng +4
We present a spatial and angular Gaussian based representation and a triple splatting process, for real-time, high-quality novel lighting-and-view synthesis from multi-view point-l…
ElastoGen: 4D Generative Elastodynamics
Yutao Feng, Yintong Shang, Xiang Feng +7
We present ElastoGen, a knowledge-driven AI model that generates physically accurate 4D elastodynamics. Unlike deep models that learn from video- or image-based observations, Elast…
Gaussian Splashing: Unified Particles for Versatile Motion Synthesis and Rendering
Yutao Feng, Xiang Feng, Yintong Shang +8
We demonstrate the feasibility of integrating physics-based animations of solids and fluids with 3D Gaussian Splatting (3DGS) to create novel effects in virtual scenes reconstructe…