Name
Abstract | ||
|---|---|---|
We present a novel approach that constructs 3D virtual garment models from photos. Our approach only requires two images as input, one front and one back. We first apply a multi-task learning network that jointly predicts fashion landmarks and parses a garment image into semantic parts. The predicted landmarks are used for deforming a template mesh to generate 3D garment model. The semantic parts are utilized for extracting color textures for the model. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/VR.2019.8797810 | 2019 26TH IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES (VR) |
Keywords | Field | DocType |
landmark prediction, part segmentation, 3D modeling | Computer vision,Computing Methodologies,Segmentation,Computer science,Artificial intelligence,Landmark,Computer graphics,3D modeling,Learning network | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||