3 citations · 4 across the 2 of their papers we have counts for
6 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…
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…
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'…
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…
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…
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…