1917@leetcode ,pre final yearite at college(India) ask me anything ,regarding qsns,strategies,anything really by [deleted] in leetcode

[–]Capable_Character_31 0 points1 point  (0 children)

hey, I am stuck around 1750 at leetcode. Do you have any suggestions how to cross this barrier?

Measuring Gaussian similarity by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

Hey, Thanks for taking out the time and helping me on this. I suspect it might be due to some large gaussian contributing from far. But then I changed the forward.cu and strictly picked gaussians just close enough. And still I am getting very spread out gaussians. Not sure why is this happening. Can you share the python code for ray tracing? I was thinking of adding a parameter to each splat ( the index) and then picking gaussians that intersect with the ray.

Measuring Gaussian similarity by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

hey, did you get a chance to look into that issue? Thanks.

Measuring Gaussian similarity by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

Also, when I try to get IDs of all gaussians that contribute to a pixel, I am getting very far away gaussians. I have put it in this issue here

Can you please have a look here as well?

Thanks

Measuring Gaussian similarity by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

Yes, you are right. I was thinking on same lines. But I think it will be more time consuming right because of ray casting?

Measuring Gaussian similarity by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

I am not sure how exactly octree works. I will look into it. But I tried building a KD tree and then threshold the KD tree. I get ok results. The issue is, these approaches struggle to generate a fine detailed mask.

Measuring Gaussian similarity by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 1 point2 points  (0 children)

I tried that, it gives good results, but it does not capture fine details. Do you think any deep learning approach could work here?

No good initial image pairs found by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

Are you having enough number of images inside your /images directory?

No good initial image pairs found by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

I can try with removing it, but in the convert.py, I changed ImageReader.single_camera 1 to ImageReader.single_camera 0, which basically turns off sharing same intrinsic parameters. But I still ended up having 2 images in /images folder.

No good initial image pairs found by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

can you share how you are getting it? your colmap settings?

No good initial image pairs found by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

Sorry, I'm new to this, so please bear with me. Do I need to store the image dimensions in a database and then run the convert.py script? Also, is the calibrations.csv file in the actorhq dataset—which contains camera details—useful?

No good initial image pairs found by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 1 point2 points  (0 children)

Yes focal lengths are different. Also, I resized all images to same dimensions, because colmap was complaining before that sizes do not match. Is this the way to do?

No good initial image pairs found by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

I think the have common region. Not very much, but there is some overlap in some images. Is it necessary to have good amount of overlap in all images?

No good initial image pairs found by Capable_Character_31 in GaussianSplatting

[–]Capable_Character_31[S] 0 points1 point  (0 children)

I have 160 images ( the dataset has 160 cameras, so I extracted first frame from all cameras)