Comments (1)
Hi @Yannnnnnnnnnnn only using patchmatch layer itself by taking raw RGB color as input would not provide robust disparity estimation. This is same for conventional patchmatch, as these nearest neighbor field method relies on robust feature representation. Please refer to deeppruner folder to see how to build a reliable and efficient stereo estimation network.
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Related Issues (20)
- RuntimeError: Error(s) in loading state_dict for DataParallel: Missing key(s) in state_dict: "module.feature_extraction.branch1.1.0.weight", HOT 2
- Test image size problem HOT 4
- Default maximum disparity HOT 2
- Parameters: input size, output size, in/out channels, stride and padding for all the layers HOT 2
- IndexError: list index out of range HOT 2
- Deep Pruner Fast on Jetson Series HOT 1
- pre-trained model HOT 1
- tuple indices must be integers or slices, not tuple HOT 1
- Cannot unpack pre-trained models from provided links. HOT 1
- Test my own dataset HOT 1
- Inference speed is much faster than reported in the paper? and the EPE performance is worse? HOT 3
- Issue in reading pfm files HOT 3
- Export to ONNX HOT 1
- submission_kitti.py
- About the training on KITTI HOT 2
- How
- How to understand the one hot filter?
- The source file is corrupt HOT 1
- Experiment on pytorch2.0.0 HOT 1
- question about the refer output of model HOT 2
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