Argmax在反向传播时是不可导的,因此,采用soft Argmax,最终返回每一个像素在cost-volume中的最大值的位置索引。 3.2无监督学习框架 初次计算匹配结果时,网络的参数是随机选取的或者是采用DeepMatching的方法。 对网络的训练是通过不断迭代完成的,在每一次迭代t中,计算从左图到右图的匹配和右图到左图的匹配,然后选择...
Unsupervised Learning of Stereo MatchingMotivation 目前众多利用深度学习进行深度估计的文章都是利用带有GT dispartiy的数据这种数据很难获取,一般会利用公开数据集,带来的问题如下:数据很少场景固定,无法…
We additionally propose cooperative unsupervised learning of occlusion and disparity, based on a different hybrid loss enforcing them to be consensus and trained alternatively to reach convergence. The comprehensive experimental analyses show that our method achieves state-of-the-art results among ...
Training Phase Shangzhe Wu Christian Rupprecht Andrea Vedaldi Visual Geometry Group, University of Oxford {szwu, chrisr, vedaldi}@robots.ox.ac.uk Testing Phase Single views only Input 3D reconstruction Textured Re-lighting Figure 1: Unsupervised learning of 3D defo...
deep-learningunsupervisedstereodata-augmentationdepth-estimationmonodepthself-supervisedmonocularmonocular-depth-estimation UpdatedOct 17, 2021 Python This repository tries to provide unsupervised deep learning models with Pytorch deep-learningunsupervisedpytorchgenerative-adversarial-networkautoencoderdenoising-autoencoder...
Recently, there are emerging many stereo matching methods for autonomous driving based on unsupervised learning. Most of them take advantage of reconstruction losses to remove dependency on disparity groundtruth. Occlusion handling is a challenging problem in stereo matching, especially for unsupervised met...
At present, deep learning has been applied more and more in monocular image depth estimation and has shown promising results. The current more ideal method for monocular depth estimation is the supervised learning based on ground truth depth, but this method requires an abundance of expensive ground...
Here we explore the intriguing possibility that visual systems might be able to discover the operation of distal scene variables by learning statistical regularities in proximal images rather than by learning an explicit mapping between proximal cues and known distal causes. Specifically, we show that ...
Unsupervised Learning of Stereo Matching. In Proceedings of the IEEE International Conference on Computer Vision, Venice, Italy, 22–29 October 2017; pp. 1576–1584. [Google Scholar] Li, A.; Yuan, Z. Occlusion Aware Stereo Matching via Cooperative Unsupervised Learning. In Proceedings of the ...
Preliminary FlowNet :一个用于预测光流的CNN网络。Supervised。 Learning Optical Flow with Convolutional Networksarxiv.org/abs/1504.06852 Unsupervised Learning of Optimal Flow: 在 FlowNetS 后面加上Unsupervised 模块。但是没有解决Occlusion和 large motion 的问题。