44 citations · 73 across the 12 of their papers we have counts for
13 papers
EASE: Parametric garment design with explicit and local ease control
Kristijan Bartol, Frieda Hentschel, Nataliya Sadretdinova +4
Garment fit and comfort depend critically on ease, the local allowance of excess material relative to the body. In existing design pipelines, ease is typically a byproduct of geome…
Im2SurfTex: Surface Texture Generation via Neural Backprojection of Multi-View Images
Yiangos Georgiou, Marios Loizou, Melinos Averkiou +1
We present Im2SurfTex, a method that generates textures for input 3D shapes by learning to aggregate multi-view image outputs produced by 2D image diffusion models onto the shapes'…
Pix2Poly: A Sequence Prediction Method for End-to-end Polygonal Building Footprint Extraction from Remote Sensing Imagery
Yeshwanth Kumar Adimoolam, Charalambos Poullis, Melinos Averkiou
Extraction of building footprint polygons from remotely sensed data is essential for several urban understanding tasks such as reconstruction, navigation, and mapping. Despite sign…
ShapeWords: Guiding Text-to-Image Synthesis with 3D Shape-Aware Prompts
Dmitry Petrov, Pradyumn Goyal, Divyansh Shivashok +3
We introduce ShapeWords, an approach for synthesizing images based on 3D shape guidance and text prompts. ShapeWords incorporates target 3D shape information within specialized tok…
GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis
Dmitry Petrov, Pradyumn Goyal, Vikas Thamizharasan +5
We introduce GEM3D -- a new deep, topology-aware generative model of 3D shapes. The key ingredient of our method is a neural skeleton-based representation encoding information on b…
FacadeNet: Conditional Facade Synthesis via Selective Editing
Yiangos Georgiou, Marios Loizou, Tom Kelly +1
We introduce FacadeNet, a deep learning approach for synthesizing building facade images from diverse viewpoints. Our method employs a conditional GAN, taking a single view of a fa…
Data Leakage Detection and De-duplication in Large Scale Geospatial Image Datasets
Yeshwanth Kumar Adimoolam, Charalambos Poullis, Melinos Averkiou
In our study, we conducted a comprehensive analysis of three widely used datasets in the domain of building footprint extraction using deep neural networks: the INRIA Aerial Image…
Projective Urban Texturing
Yiangos Georgiou, Melinos Averkiou, Tom Kelly +1
This paper proposes a method for automatic generation of textures for 3D city meshes in immersive urban environments. Many recent pipelines capture or synthesize large quantities o…
BuildingNet: Learning to Label 3D Buildings
Pratheba Selvaraju, Mohamed Nabail, Marios Loizou +5
We introduce BuildingNet: (a) a large-scale dataset of 3D building models whose exteriors are consistently labeled, (b) a graph neural network that labels building meshes by analyz…
Learning Part Boundaries from 3D Point Clouds
Marios Loizou, Melinos Averkiou, Evangelos Kalogerakis
We present a method that detects boundaries of parts in 3D shapes represented as point clouds. Our method is based on a graph convolutional network architecture that outputs a prob…
Cross-Shape Attention for Part Segmentation of 3D Point Clouds
Marios Loizou, Siddhant Garg, Dmitry Petrov +2
We present a deep learning method that propagates point-wise feature representations across shapes within a collection for the purpose of 3D shape segmentation. We propose a cross-…
Learning Material-Aware Local Descriptors for 3D Shapes
Hubert Lin, Melinos Averkiou, Evangelos Kalogerakis +5
Material understanding is critical for design, geometric modeling, and analysis of functional objects. We enable material-aware 3D shape analysis by employing a projective convolut…
3D Shape Segmentation with Projective Convolutional Networks
Evangelos Kalogerakis, Melinos Averkiou, Subhransu Maji +1
This paper introduces a deep architecture for segmenting 3D objects into their labeled semantic parts. Our architecture combines image-based Fully Convolutional Networks (FCNs) and…