Comments (3)
For slant GT generation, I use at least square and RANSAC to fit the plane within each patch of disp GTs. Since it requires a lot of computation, I implement this in CUDA & C++ (where the pybind is also needed). I will upload the latest version of my project and the slant GT generation code these days. Stay tuned. :)
from pytorch-hitnet-hierarchical-iterative-tile-refinement-network-for-real-time-stereo-matching.
This is really great, Looking forward to your latest version~
from pytorch-hitnet-hierarchical-iterative-tile-refinement-network-for-real-time-stereo-matching.
This is really great, Looking forward to your latest version~
Excuse me, could you have gotten slant GTs?I have trouble in compiling the codes which MJITG uploaded
from pytorch-hitnet-hierarchical-iterative-tile-refinement-network-for-real-time-stereo-matching.
Related Issues (10)
- I'm having trouble in inference
- The code for slant parameter generation is Require access rights HOT 1
- "maxdisp" in initialization_loss.py HOT 1
- Cuda error: device-side assert triggered HOT 4
- Data inconsistency HOT 1
- Great work! The performance details HOT 2
- question in class DispUpsampleBySlantedPlane
- Pretrained models HOT 1
- request for video demonstration of paper
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from pytorch-hitnet-hierarchical-iterative-tile-refinement-network-for-real-time-stereo-matching.