Deep Convolutional Encoder Decoder Architecture
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Generative Adversarial Text to Image Synthesis
proceedings.mlr.pressdeep convolutional decoder networks to generate realistic images.Dosovitskiy et al.(2015) trained a deconvolutional network (several layers of convolution and upsampling) to generate 3D chair renderings conditioned on a set of graph-ics codes indicating shape, position and lighting.Yang et al. (2015) added an encoder network as well as actions ...
Rethinking Semantic Segmentation From a Sequence-to ...
openaccess.thecvf.coma fully-convolutional network (FCN) with an encoder-decoder architecture. The encoder progressively reduces the spatial resolution and learns more abstract/semantic visual concepts with larger receptive fields. Since context modeling is critical for segmentation, the latest efforts have been focused on increasing the receptive field, through ei-
D-LinkNet: LinkNet With Pretrained Encoder and Dilated ...
openaccess.thecvf.comThe decoder of D-LinkNet remains the same as the orig-inal LinkNet [15], which is computationally efficient. The decoder part uses transposed convolution [27] layers to do upsampling, restoring the resolution of feature map from 32×32to 1024×1024. 2.2. Pretrained Encoder Transfer learning is an efficient method for computer vi-