Comments (2)
Okay. I don't think it's easy to tell which one has worse 'depth' in this example.
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Just to confirm, I wasn't saying is worst, I should be more specific, the one on top fits better to the original scene, the depth spreads linear on reconstruction, it doesn't match but is close to ground truth.
The second doesn't look linear on reconstruction, most of the data is concentrated in planes, doesn't spread uniformly, I was assuming there must be some gamma issue when interpreting the result.
Assumed models trained on same dataset will give very much similar result, I can provide more details about scene reconstruction.
from boostingmonoculardepth.
Related Issues (20)
- Nan values on evaluation code HOT 1
- Parallel Local Boosting? HOT 1
- the color is different HOT 1
- Evaluate prediction depth on KITTI dataset using evaluatedataset.m HOT 2
- depth numerical array HOT 1
- GPU thresh hold for nvidia A100 ?? HOT 2
- RuntimeError: The size of tensor a (75) must match the size of tensor b (76) at non-singleton dimension 3 HOT 4
- Code section2 error HOT 5
- Temporal inconsistency on image sequences HOT 4
- Can we use this for video input? HOT 1
- Issue max res 720 * 1280 ? HOT 8
- How to speed up the inference? HOT 2
- License of output images HOT 2
- Feature Request: Run on CPU or MPS for Apple M1/M2 HOT 4
- Unable to download mergenet model weights HOT 2
- Bit depth and banding HOT 2
- Which one of MiDas, DPT and LeRes is better for monocular depth estimation and takes the shortest time? HOT 1
- What's the parameter to be set in demo.py for "(NEW!) Now you can set the maximum resolution of the results to reduce runtime" HOT 1
- Why does NAN appear in the model inference process HOT 2
- Depth map by LeRes HOT 1
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