JiaRenChang/PSMNet
A PyTorch implementation of a CNN architecture for estimating depth from stereo image pairs.
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PSMNet implements a pyramid stereo matching network that uses spatial pyramid pooling to aggregate global context at multiple scales and a 3D CNN with stacked hourglass networks to regularize cost volumes for disparity estimation. The model takes stereo image pairs as input and outputs per-pixel depth estimates, demonstrating that global context information helps resolve ambiguity in matching regions. This is a supervised learning approach for disparity prediction using convolutional neural networks trained on stereo datasets.
Frequently asked
- What is JiaRenChang/PSMNet?
- A PyTorch implementation of a CNN architecture for estimating depth from stereo image pairs.
- Is PSMNet open source?
- Yes — JiaRenChang/PSMNet is open source, released under the MIT license.
- What language is PSMNet written in?
- JiaRenChang/PSMNet is primarily written in Python.
- How popular is PSMNet?
- JiaRenChang/PSMNet has 1.5k stars on GitHub.
- Where can I find PSMNet?
- JiaRenChang/PSMNet is on GitHub at https://github.com/JiaRenChang/PSMNet.