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Occupancy Networks: Learning 3D Reconstruction in Function Space
TLDR
In this paper, we propose Occupancy Networks, a new representation for learning-based 3D reconstruction methods based on learning a continuous 3D occupancy function. Expand
Differentiable Volumetric Rendering: Learning Implicit 3D Representations Without 3D Supervision
TLDR
In this work, we propose a differentiable rendering formulation for implicit shape and texture representations. Expand
Convolutional Occupancy Networks
TLDR
In this paper, we propose Convolutional Occupancy Networks, a more flexible implicit representation for detailed reconstruction of objects and 3D scenes. Expand
Texture Fields: Learning Texture Representations in Function Space
TLDR
In this paper, we propose Texture Fields, a novel texture representation which is based on regressing a continuous 3D function parameterized with a neural network. Expand
Occupancy Flow: 4D Reconstruction by Learning Particle Dynamics
TLDR
We present Occupancy Flow, a novel spatio-temporal representation of time-varying 3D geometry with implicit correspondences. Expand
GRAF: Generative Radiance Fields for 3D-Aware Image Synthesis
TLDR
In this paper, we propose a generative model for radiance fields which have recently proven successful for novel view synthesis of a single scene. Expand
GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields
TLDR
We introduce GIRAFFE, a novel method for generating scenes in a controllable and photorealistic manner while training from raw unstructured image collections. Expand
Learning Implicit Surface Light Fields
TLDR
We propose Conditional Implicit Surface Light Fields (cSLF), a novel implicit representation for capturing the visual appearance of an object in terms of its surface light field. Expand
Automatic Semantic Labelling of Images by Their Content Using Non-Parametric Bayesian Machine Learning and Image Search Using Synthetically Generated Image Collages
TLDR
In this paper, we describe a novel algorithm for fully unsupervised discovery of meaningful object categories in images and their semantic labelling. Expand
Supplementary Material for Occupancy Networks : Learning 3 D Reconstruction in Function Space
In this supplementary document, we first give a detailed overview of our architectures and training procedure in Section 1. We then discuss our implementation of the baselines in Section 2 andExpand
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