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cs.CV2023
Progressive Learning of 3D Reconstruction Network from 2D GAN Data
Aysegul Dundar, Jun Gao, Andrew Tao +1
This paper presents a method to reconstruct high-quality textured 3D models from single images. Current methods rely on datasets with expensive annotations; multi-view images and t…
cs.CV2016★ 143 cited
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
Song Han, Jeff Pool, Sharan Narang +9
Modern deep neural networks have a large number of parameters, making them very hard to train. We propose DSD, a dense-sparse-dense training flow, for regularizing deep neural netw…