Training Batch-size and time about differentiable_volumetric_rendering HOT 2 CLOSED

Hi @JiejiangWu , Thanks a lot for your message and interest!

Here an excerpt from our paper: "We train on a single NVIDIA V100GPU with a batch size of 64 images with1024 random pixels each."

So in the single-view reconstruction experiments, we train with a batch size of 64, and per object, we sample 1024 pixels. We train on a single V100 GPU (we did not perform multi-GPU training). We let the the big models train for quite a long time (2 - 5 weeks). These numbers do not apply to the multi-view reconstruction experiments.

If you want to train on smaller GPUs or with less time, you can use a decoder with a smaller hidden dimension, e.g. 128, by adding

model:
  decoder_kwargs:
    hidden_size: 128

to your config file.

I hope this helps. Good luck with your research!

from differentiable_volumetric_rendering.

Oh, sorry! I messed up the batch-size in the paper. You are right.
Your reply solves my concerns. I think this issue can be closed.

from differentiable_volumetric_rendering.