Comments (2)
More rendered pic can be found:
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Hi @boxuLibrary, I think it's probably because the baseline between the input views is too wide. When training on RE10K, we assume there are enough overlaps between the input source views, which we achieve by constraining the frame distance.
Below is a typical example of the overlap between the RE10K input views. The second column shows the regions that overlap with the other input view.
You can test on two other input views with larger overlaps, similar to the one we chose for the DTU testing. That should work better.
You can also visualize the overlaps between the input by using the code snippets from the pixelSplat project at here.
Still, these are interesting findings, although I do expect that the released model might not perform well on object-centric scenes since it is trained on RE10K. I might also find time to look into the CO3D dataset, but no guarantee...
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Related Issues (20)
- Function of times_per_scene HOT 1
- about training with multi GPU HOT 4
- Resolution Requirements HOT 2
- why fix the fx and fy when center-crop the image patch in the code? HOT 2
- How to generate `evaluation_index_re10k.json` and `evaluation_index_re10k_video.json`? HOT 2
- how can i do reference if i have one picture and it's corresponding pose? HOT 2
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- Hi! How can I visualize the ply file with RGB colors? HOT 3
- Question about rendering depth from the predicted gaussians HOT 2
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- About the interactive viewers HOT 2
- how can i infer on my own dataset? HOT 1
- Question about custom dataset finetuning HOT 4
- Asking about range of depth map prediction value HOT 2
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- Expanding to Autonomous Driving Datasets HOT 1
- skipped bad example when using acid dataset HOT 1
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