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Efficient Metropolis Path Sampling for Material Editing and Re-rendering
(The Eurographics Association, 2018)
This paper proposes efficient path sampling for re-rendering scenes after material editing. The proposed sampling method is based on Metropolis light transport (MLT) and distributes more path samples to pixels whose values ...
Maximum-Clearance Planar Motion Planning Based on Recent Developments in Computing Minkowski Sums and Voronoi Diagrams
(The Eurographics Association, 2021)
We present a maximum-clearance motion planning algorithm for planar geometric models with three degrees of freedom (translation and rotation). This work is based on recent developments in real-time algorithms for computing ...
External Forces Guided Fluid Surface and Volume Reconstruction from Monocular Video
(The Eurographics Association, 2019)
We propose a novel method to reconstruct fluid's volume movement and surface details from just a monocular video for the first time. Although many monocular video-based reconstruction methods have been developed, the ...
Neural Proxy: Empowering Neural Volume Rendering for Animation
(The Eurographics Association, 2021)
Achieving photo-realistic result is an enticing proposition for the computer graphics community. Great progress has been achieved in the past decades, but the cost of human expertise has also grown. Neural rendering is a ...
Modeling Detailed Cloud Scene from Multi-source Images
(The Eurographics Association, 2018)
Realistic cloud is essential for enhancing the quality of computer graphics applications, such as flight simulation. Data-driven method is an effective way in cloud modeling, but existing methods typically only utilize one ...
Progressive 3D Scene Understanding with Stacked Neural Networks
(The Eurographics Association, 2018)
3D scene understanding is difficult due to the natural hierarchical structures and complicated contextual relationships in the 3d scenes. In this paper, a progressive 3D scene understanding method is proposed. The scene ...
SM-NET: Reconstructing 3D Structured Mesh Models from Single Real-World Image
(The Eurographics Association, 2021)
Image-based 3D structured model reconstruction enables the network to learn the missing information between the dimensions and understand the structure of the 3D model. In this paper, SM-NET is proposed in order to reconstruct ...
Robust and Efficient SPH Simulation for High-speed Fluids with the Dynamic Particle Partitioning Method
(The Eurographics Association, 2018)
In this paper, our research efforts are devoted to the efficiency issue of the SPH simulation when the ratio of velocities among fluid particles is large. Specifically, we introduce a k-means clustering method into the SPH ...
Feature Curve Network Extraction via Quadric Surface Fitting
(The Eurographics Association, 2019)
Feature curves on 3D shapes provide a high dimensional representation of the geometry and reveal their underlying structure. In this paper, we present an automatic approach for extracting complete feature curve networks ...
A Deep Learned Method for Video Indexing and Retrieval
(The Eurographics Association, 2018)
In this paper, we proposed a deep neural network based method for content based video retrieval. Our approach leveraged the deep neural network to generate the semantic information and introduced the graph-based storage ...