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A very impressive job. I saw in the explanation that there are two stages: training and testing, and in the provided trained file names, the trained model files all have an item name, such as "car", "chair", etc. May I ask if the method of our paper is to train a model for each type of item to generate a new model? I think this is a good idea, and I would also like to ask if it is possible to use the training code to train the model of the object I want, such as a robot. Thank you.
The text was updated successfully, but these errors were encountered:
Hi! While the presented models are all trained on single-category datasets, SSDNeRF could also generalize to multi-category datasets (preferably with additional unet conditioning). There's no hard limit on what types of models you can train on.
A very impressive job. I saw in the explanation that there are two stages: training and testing, and in the provided trained file names, the trained model files all have an item name, such as "car", "chair", etc. May I ask if the method of our paper is to train a model for each type of item to generate a new model? I think this is a good idea, and I would also like to ask if it is possible to use the training code to train the model of the object I want, such as a robot. Thank you.
The text was updated successfully, but these errors were encountered: