excuse me， I used the pre packaged model provided in readme for inference without making any changes to the code, and the result I obtained was fuzzy without any changes to the code. What could be the reason for this?

[songofjoy]

excuse me， I used the pre-trained model provided in readme for inference without making any changes to the code, and the result I obtained was fuzzy without any changes to the code. What could be the reason for this?

pre-trained model:
dl3dv_480p.ckpt

run :

dl3dv; requires at least 22G VRAM

python -m src.main +experiment=dl3dv_mvsplat360
wandb.name=dl3dv_480P_ctx5_tgt56
mode=test
dataset/view_sampler=evaluation
dataset.roots=[datasets/dl3dv_tiny]
checkpointing.load=checkpoints/dl3dv_480p.ckpt

[donydchen]

Hi @songofjoy, would you mind sharing some of your results here? MVSplat360 is, of course, not a perfect solution for every scene, but the released model should be able to render results similar to those in the demo video. If the results you obtained are much worse, then something unexpected might happen in the working environment.

[songofjoy]

[donydchen]

Hi @songofjoy, I just rerun the test on my machine using the latest released codes. Below are the outputs I obtained regarding the two images you shared.

These align well with the results posted in #9 by other users. Hence, the errors might be caused by your experimental environment. I reckon the 3DGS rendering is correctly set on your side, and the problem comes from the SVD part.

You might reinstall the mvsplat360 virtual environment and see whether it resolves the issue. FYI, I use the latest 3DGS renderer and SVD codes. Hope it helps.

[songofjoy]

Thank you very much, I will try to reconfigure the running environment.