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### Specifications like the version of the project, operating system, and hardware
CPU: Intel(R) Core(TM) i5-8259U CPU @ 2.30GHz (8 cores)
RAM: 8.00GB Physical Memory 8.00GB Virtual Memory
OS: Da…
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console.txt:
[INFO] DTM is turned on, automatically turning on point cloud classification
[INFO] Initializing ODM 3.3.4 - Tue Dec 19 07:28:59 2023
[INFO] ==============
[INFO] 3d_ti…
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Hi,
thanks for the amazing work.
I tried to apply this work to real-time reconstruction, but I found that the mapping of each frame was quite time-consuming (Similar to the results in Table 6 whic…
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Please check whether this paper is about 'Voice Conversion' or not.
## article info.
- title: **An Adaptive Learning based Generative Adversarial Network for One-To-One
Voice Conversion**
- summary:…
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Hi @chaytonmin, thanks for releasing the code!
I am trying to train the Voxel-MAE model on KITTI dataset, and try to visualize the reconstruction results. Here is a example I got at epoch30:
![i…
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Thank you for your nice work!
I got a cuda error when I trying to train this model. It's fine for me to train a vanilla Gaussian Splatting and some other Gaussian Splatting models. Just wonder what…
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Hi,
Thanks for the great work. Here I show the results on Barn. Hope it helps.
1. Generated dense point clouds.
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2. Predicted mesh after training for half an hour with [this comm…
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Nice job. I tested your code on an open source which could be download from https://doc.arcgis.com/en/drone2map/latest/help/sample-data.htm.
But the reconstructed geometry is not so reasonable. Is …
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It seems that Kimera-VIO only produce an optimized pose for each keyframe, and only fuse the keyframes to Kimera-semantics module. So the map will not be as dense as general 3d reconstruction, right?
…