chowkamlee81 commented on issue #7717: Subpixel convolution(state of art) implementation rather than using Deconvolution. URL: https://github.com/apache/incubator-mxnet/issues/7717#issuecomment-329814975 Thanks for your reply .. featmap_score = mx.symbol.Convolution(data=upsampling_featmap, kernel=(1, 1), pad=(0, 0), stride = (1, 1),num_filter=num_classes, name="featmap_score",no_bias = True) **# Dimensions (1,19,768,1024)** croped_score = mx.symbol.Crop(*[featmap_score, data], offset=(8, 8), name='croped_score') **# Dimensions (1,19,768,1024)** Crop is done so that for other datasets it should be compatible with i/p dimensions. In this scenario, before and after crop dimensions remains same since network is adjusted to work for this dataset i.e multiples of 2,4,8etc. **Hence kindly suggest if you have any ideas since iam trying hard** ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
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