Comments (3)
HI! Of course you could make an attempt. In our two-branch (actually hourglass-styled) backbone, the second (DD) branch could be regarded as a reprocessing procedure of the first (CD) branch prediction, which is actually a coarse predicted depth. Therefore, you could either feed the hand-crafted one into the second branch or even add a new third branch. And the third branch would function similarly as the second branch.
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Thank you so much, I will give a try as you suggested.
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Hi, @JUGGHM , sorry to ask you this question again, I want to back project the predicted depth map to point cloud coordinates, is that possible ? if so, can you give me code for back projection like input will be predicted depth map and output will be point cloud which will be denser in front view. Thank you.
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Related Issues (20)
- Runtime measurement HOT 4
- How to use the sparse depth?
- How to use the sparse depth? HOT 4
- Modify the backbone network HOT 3
- lightweight deployment of PENet network
- How to infer PENet for KITTI object task? HOT 3
- broken PNG file HOT 1
- the difference intrinsic parameters between train and test HOT 4
- Modify DA-CSPN++ for single branch input HOT 1
- some questions about the implement of CSPN HOT 4
- Model mismatch at inference time HOT 1
- Tensor Dimension Mismatch HOT 1
- How many parameters dose PENet have? HOT 2
- About training HOT 1
- How to implement the model with ROS?
- can't download the pretrained PENet Model
- Pretrained on NYU dataset?
- RuntimeError: CUDA out of memory.
- confindence map
- lower lidar scanline input
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