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TensorFlow implementation of DispNet by Zhijian Jiang.

DispNet-TensorFlow

TensorFlow implementation of A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation by Zhijian Jiang.

Dataset

Tutorials

TensorFlow

Network

Convolutional Network

Name Kernel Strides Channels I/O Input Resolution Output Resolution Input
conv1 7 * 7 1 6/64 1536 * 768 768 * 384 Images
max_pool1 2 * 2 2 64/64 1536 * 768 768 * 384 conv1
conv2 5 * 5 1 64/128 768 * 384 384 * 192 max_pool1
max_pool2 2 * 2 2 128/128 768 * 384 384 * 192 conv2
conv3a 5 * 5 1 128/256 384 * 192 192 * 96 max_pool2
max_pool3 2 * 2 2 256/256 384 * 192 192 * 96 conv3a
conv3b 3 * 3 1 256/256 192 * 96 192 * 96 max_pool3
conv4a 5 * 5 1 256/512 192 * 96 96 * 48 conv3b
max_pool4 2 * 2 2 512/512 96 * 48 96 * 48 conv4a
conv4b 3 * 3 1 512/512 96 * 48 96 * 48 max_pool4
conv5a 5 * 5 1 512/512 96 * 48 48 * 24 conv4b
max_pool5 2 * 2 2 512/512 48 * 24 48 * 24 conv5a
conv5b 3 * 3 1 512/512 48 * 24 48 * 24 max_pool5
conv6a 5 * 5 1 512/512 48 * 24 24 * 12 conv5b
max_pool6 2 * 2 2 1024/1024 24 * 12 24 * 12 conv6a
conv6b 3 * 3 1 1024/1024 24 * 12 24 * 12 max_pool6
pr6 + loss6 3 * 3 1 1024/1 24 * 12 24 * 12 conv6b

Upconvolutional Network

Name Kernel Strides Channels I/O Input Resolution Output Resolution Input
upconv5 4 * 4 2 1024/512 24 * 12 48 * 24 conv6b
iconv5 3 * 3 1 1024/512 48 * 24 48 * 24 upconv5 + conv5b
pr5+loss5 3 * 3 1 512/1 48 * 24 48 * 24 iconv5
upconv4 4 * 4 2 512/256 48 * 24 96 * 48 iconv5
iconv4 3 * 3 1 768/256 96 * 48 96 * 48 upconv4 + conv4b
pr4+loss4 3 * 3 1 512/1 96 * 48 96 * 48 iconv4
upconv3 4 * 4 2 256/128 96 * 48 192 * 96 iconv4
iconv3 3 * 3 1 384/128 192 * 96 192 * 96 upconv3 + conv3b
pr3+loss3 3 * 3 1 128/1 192 * 96 192 * 96 iconv3
upconv2 4 * 4 2 128/64 192 * 96 384 * 192 iconv3
iconv2 3 * 3 1 192/64 384 * 192 384 * 192 upconv2 + conv2
pr2+loss2 3 * 3 1 64/1 384 * 192 384 * 192 iconv2
upconv1 4 * 4 2 64/32 384 * 192 768 * 384 iconv2
iconv1 3 * 3 1 96/32 768 * 384 768 * 384 upconv1 + conv1
pr1+loss1 3 * 3 1 32/1 768 * 384 768 * 384 iconv1

Issues

  • How to input png images:

    ontents = ''
ith open('path/to/image.jpeg') as f:
		contents = f.read()
f.image.decode_jpeg(contents) 

    eader = tf.WholeFileReader(http://stackoverflow.com/questions/34340489/tensorflow-read-images-with-labels)
	key, value = reader.read(filename_queue)
	example = tf.image.decode_png(value)

    	file_contents = tf.read_file(input_queue[0])
example = tf.image.decode_png(file_contents, channels=3)

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verified publisher icon ZhijianJiang

Metadata

TensorFlow implementation of DispNet by Zhijian Jiang.

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