Comments (3)
Hello, thank you for your interest in the paper. Yes I have code somewhere on my computer however it is rather hard-coded at the moment, but here is the general idea if you want to generate the same figures (actually some explainations are in supplementary materials).
- Choose your image I1, and compute the estimated depth D1 with SharpNet
- Render a depth map D_bunny and an RGB image I_bunny of the Stanford Bunny using this ply model and a renderer of your choice (i used Blender), using an object pose of your choice.
- Compute the new RGB image I2 that is a copy of I1 but with
I2[D_bunny<D1] = I_bunny[D_bunny<D1]
This should put pixels of the rendered bunny image instead of original the image when the scene is occluded by the bunny, and vice/versa. - Look at your image and see if the bunny is at the distance you hoped it would be in the image, if not, repeat from 2.
I am sorry if you were looking more for a true augmented reality method, I may do that later for sequence of registered images but not in a little while.
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Hello, Michael, thank you for your reply! Do you use contours on step 3? What do you mean by designation D1?
from sharpnet.
Hey, sorry for the late reply. No I do not use contours in step 3, only depth prediction. As for D1, it denotes the predicted depth map with SharpNet.
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Related Issues (15)
- Normalization deph image
- [BUG] Evaluation bug in eval.py compute_depth_metrics() HOT 2
- [Question] Could you explain the normalization scheme you have used for PBRS and NYUV2 ? HOT 2
- What's the --scale option means when run the demo.py? HOT 3
- How to get the real absolute depth from your model ? HOT 2
- Dear author, is it necessary to have a pretraining model of PBRS for training? HOT 3
- Normal ground-truth for NYU dataset? HOT 1
- why can't predict occluding contours? HOT 7
- About your loss function and finetuning HOT 3
- Optimizer and Weight decay HOT 2
- Strange Output Artefacts HOT 2
- [Question] Do you have any result or plan on KITTI HOT 1
- About the depth-boundary consistency loss HOT 2
- Question: Annotation tool HOT 3
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