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PCPNet: Learning Local Shape Properties from Raw Point Clouds
(The Eurographics Association and John Wiley & Sons Ltd., 2018)
In this paper, we propose PCPNET, a deep-learning based approach for estimating local 3D shape properties in point clouds. In contrast to the majority of prior techniques that concentrate on global or mid-level attributes, ...
Deep Learning for Graphics
(The Eurographics Association, 2018)
In computer graphics, many traditional problems are now better handled by deep-learning based data-driven methods. In applications that operate on regular 2D domains, like image processing and computational photography, ...
Computational Design and Optimization of Non-Circular Gears
(The Eurographics Association and John Wiley & Sons Ltd., 2020)
We study a general form of gears known as non-circular gears that can transfer periodic motion with variable speed through their irregular shapes and eccentric rotation centers. To design functional non-circular gears is ...
RigidFusion: RGB-D Scene Reconstruction with Rigidly-moving Objects
(The Eurographics Association and John Wiley & Sons Ltd., 2021)
Although surface reconstruction from depth data has made significant advances in the recent years, handling changing environments remains a major challenge. This is unsatisfactory, as humans regularly move objects in their ...
Towards a Neural Graphics Pipeline for Controllable Image Generation
(The Eurographics Association and John Wiley & Sons Ltd., 2021)
In this paper, we leverage advances in neural networks towards forming a neural rendering for controllable image generation, and thereby bypassing the need for detailed modeling in conventional graphics pipeline. To this ...
POP: Full Parametric model Estimation for Occluded People
(The Eurographics Association, 2019)
In the last decades, we have witnessed advances in both hardware and associated algorithms resulting in unprecedented access to volumes of 2D and, more recently, 3D data capturing human movement. We are no longer satisfied ...
MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras
(The Eurographics Association and John Wiley & Sons Ltd., 2022)
Synthesizing novel views of dynamic humans from stationary monocular cameras is a specialized but desirable setup. This is particularly attractive as it does not require static scenes, controlled environments, or specialized ...
Neurosymbolic Models for Computer Graphics
(The Eurographics Association and John Wiley & Sons Ltd., 2023)
Procedural models (i.e. symbolic programs that output visual data) are a historically-popular method for representing graphics content: vegetation, buildings, textures, etc. They offer many advantages: interpretable design ...
Factored Neural Representation for Scene Understanding
(The Eurographics Association and John Wiley & Sons Ltd., 2023)
A long-standing goal in scene understanding is to obtain interpretable and editable representations that can be directly constructed from a raw monocular RGB-D video, without requiring specialized hardware setup or priors. ...
Neural Semantic Surface Maps
(The Eurographics Association and John Wiley & Sons Ltd., 2024)
We present an automated technique for computing a map between two genus-zero shapes, which matches semantically corresponding regions to one another. Lack of annotated data prohibits direct inference of 3D semantic priors; ...