An End-to-End Conditional Generative Adversarial Network Based on Depth Map for 3D Craniofacial Reconstruction.
Niankai ZhangJunli ZhaoFuqing DuanZhenkuan PanZhongke WuMingquan ZhouXianfeng GuPublished in: ACM Multimedia (2022)
Keyphrases
- end to end
- depth map
- three dimensional
- high resolution
- multi view
- depth information
- stereo matching
- d scene
- high quality
- image sequences
- super resolution
- depth estimation
- low resolution
- view synthesis
- congestion control
- input image
- scene reconstruction
- shape from focus
- free viewpoint
- input data
- viewpoint
- real time
- bit rate
- feature extraction
- data sets