We propose Differentiable Surface Splatting (DSS), a high-fidelity differentiable renderer for point clouds. Gradients for point locations and normals are carefully designed to handle discontinuities of the rendering function. Regularization terms are introduced to ensure uniform distribution of the points on the underlying surface. We demonstrate applications of DSS to inverse rendering for geometry synthesis and denoising, where large scale topological changes, as well as small scale detail modifications, are accurately and robustly handled without requiring explicit connectivity, outperforming state-of-the-art techniques. The data and code are at this https URL
We present a novel approach for extreme simplification of point set models in the context of real-ti...
Abstract Point-based rendering approaches have gained a major interest in recent years, basically re...
Nowadays, there are multiple available range scanning technologies which can capture extremely detai...
We propose an efficient and GPU-accelerated sampling framework which enables unbiased gradient appro...
Splatting-based rendering techniques are currently the best choice for efficient high quality render...
Point-based surface representations have gained increasing interest in the computer graphics communi...
We present a novel algorithm for accurate, high quality point rendering, which is based on the formu...
International audienceSplatting-based rendering techniques are currently the best choice for efficie...
Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces...
OPAL-MesoInternational audienceThere has recently been great interest in neural rendering methods. S...
In this paper we present a powerful differentiable surface fitting technique to derive a compact sur...
International audienceIn this paper we present multiple simple and efficient improvements for splatt...
In this paper we present a novel point-based rendering approach based on object-space point interpol...
We introduce a method for surface reconstruction from point sets that is able to cope with noise and...
Modern laser range and optical scanners need rendering techniques that can handle millions of points...
We present a novel approach for extreme simplification of point set models in the context of real-ti...
Abstract Point-based rendering approaches have gained a major interest in recent years, basically re...
Nowadays, there are multiple available range scanning technologies which can capture extremely detai...
We propose an efficient and GPU-accelerated sampling framework which enables unbiased gradient appro...
Splatting-based rendering techniques are currently the best choice for efficient high quality render...
Point-based surface representations have gained increasing interest in the computer graphics communi...
We present a novel algorithm for accurate, high quality point rendering, which is based on the formu...
International audienceSplatting-based rendering techniques are currently the best choice for efficie...
Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces...
OPAL-MesoInternational audienceThere has recently been great interest in neural rendering methods. S...
In this paper we present a powerful differentiable surface fitting technique to derive a compact sur...
International audienceIn this paper we present multiple simple and efficient improvements for splatt...
In this paper we present a novel point-based rendering approach based on object-space point interpol...
We introduce a method for surface reconstruction from point sets that is able to cope with noise and...
Modern laser range and optical scanners need rendering techniques that can handle millions of points...
We present a novel approach for extreme simplification of point set models in the context of real-ti...
Abstract Point-based rendering approaches have gained a major interest in recent years, basically re...
Nowadays, there are multiple available range scanning technologies which can capture extremely detai...