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bluestyle97 avatar bluestyle97 commented on August 20, 2024

You need to train instant-nerf first. The mesh-based rendering can only provide gradients at near-surface area, making the network hard to converge. Our mesh model is finetuned from the nerf model.

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Kev1MSL avatar Kev1MSL commented on August 20, 2024

Alright makes sense thank you! I have tried the training of instant-nerf, however I am starting with cubes as first object rendered and I was wondering if the default code starts with pretrained weights for the LRM since I am starting with cubes?

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Sri-vatsa avatar Sri-vatsa commented on August 20, 2024

@Kev1MSL According to the paper, the training is initialized using openlrm weights. @bluestyle97 How many training steps have you run the training of instant-nerf for using your training data?

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Mrguanglei avatar Mrguanglei commented on August 20, 2024

@Kev1MSL Hello, please take a look at your dataset structure and training configuration file? This will help you better

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Mrguanglei avatar Mrguanglei commented on August 20, 2024

@Sri-vatsa Hello, could you take a look at the structure of your dataset and the configuration file used to train nerf? I have encountered a problem in this regard, which I cannot solve, and I need your help

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HaFred avatar HaFred commented on August 20, 2024

Alright makes sense thank you! I have tried the training of instant-nerf, however I am starting with cubes as first object rendered and I was wondering if the default code starts with pretrained weights for the LRM since I am starting with cubes?

Hi based on your graph, it seems like your training set contains only 3.5k instances, is that true? The paper says 270k instances, so do you know how to curate the dataset correctly for training instantnerf? Thanks a lot!

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