Add to ORKGImplicit neural representations of 3D shapes form strong priors that areuseful for various applications, such as single and multiple view 3Dreconstruction. A downside of existing neural representations is that theyrequire multiple network evaluations for rendering, which leads to highcomputational costs. This limitation forms a bottleneck particularly in thecontext of inverse problems, such as image-based 3D reconstruction. To addressthis issue, in this paper (i) we propose a novel hybrid 3D objectrepresentation based on a signed distance function (SDF) that we augment with adirectional distance function (DDF), so that we can predict distances to theobject surface from any point on a sphere enclosing the object. Moreover, (ii)using the prop...
Recent advances in learning 3D shapes using neural implicit functions have achieved impressive resul...
In this paper, we develop a novel 3D object recognition algorithm to perform detection and pose esti...
Scene Completion is the task of completing missing geometry from a partial scan of a scene. Most pre...
Neural 3D implicit representations learn priors that are useful for diverse applications, such as si...
Probabilistic diffusion models have achieved state-of-the-art results for image synthesis, inpaintin...
We present a novel method, called NeuralUDF, for reconstructing surfaces with arbitrary topologies f...
Neural rendering can be used to reconstruct implicit representations of shapes without 3D supervisio...
We introduce a novel approach for rendering static and dynamic 3D neural signed distance functions (...
Learning neural implicit representations has achieved remarkable performance in 3D reconstruction fr...
Recently, neural implicit surfaces learning by volume rendering has become popular for multi-view re...
Recent works on implicit neural representations have made significant strides. Learning implicit neu...
In this paper, we address the problem of multi-view 3D shape reconstruction. While recent differenti...
Neural implicit functions have recently shown promising results on surface reconstructions from mult...
Sphere tracing, introduced by Hart in [5], is an efficient method to find ray- surface intersections, ...
We present a novel neural surface reconstruction method, called NeuS, for reconstructing objects and...
Recent advances in learning 3D shapes using neural implicit functions have achieved impressive resul...
In this paper, we develop a novel 3D object recognition algorithm to perform detection and pose esti...
Scene Completion is the task of completing missing geometry from a partial scan of a scene. Most pre...
Neural 3D implicit representations learn priors that are useful for diverse applications, such as si...
Probabilistic diffusion models have achieved state-of-the-art results for image synthesis, inpaintin...
We present a novel method, called NeuralUDF, for reconstructing surfaces with arbitrary topologies f...
Neural rendering can be used to reconstruct implicit representations of shapes without 3D supervisio...
We introduce a novel approach for rendering static and dynamic 3D neural signed distance functions (...
Learning neural implicit representations has achieved remarkable performance in 3D reconstruction fr...
Recently, neural implicit surfaces learning by volume rendering has become popular for multi-view re...
Recent works on implicit neural representations have made significant strides. Learning implicit neu...
In this paper, we address the problem of multi-view 3D shape reconstruction. While recent differenti...
Neural implicit functions have recently shown promising results on surface reconstructions from mult...
Sphere tracing, introduced by Hart in [5], is an efficient method to find ray- surface intersections, ...
We present a novel neural surface reconstruction method, called NeuS, for reconstructing objects and...
Recent advances in learning 3D shapes using neural implicit functions have achieved impressive resul...
In this paper, we develop a novel 3D object recognition algorithm to perform detection and pose esti...
Scene Completion is the task of completing missing geometry from a partial scan of a scene. Most pre...