sunset1995 / DirectVoxGO

Direct voxel grid optimization for fast radiance field reconstruction.
https://sunset1995.github.io/dvgo
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Inward-facing scene poor quality - coarse model too dense #33

Open dispoth opened 2 years ago

dispoth commented 2 years ago

Hi,

I have trained an inward-facing scene of a can using 120 posed images from the YCB dataset in an equally spaced upper semi-sphere and used the 'nerf' config e.g.

_base_ = '../default.py'

expname = 'dvgo_Masterchefcan'
basedir = './logs/ycbrealworld'

data = dict(
    datadir='./data/ycbrealworld/002_master_chef_can',
    dataset_type='ycbrealworld',
    white_bkgd=True,
)

coarse_train = dict(
    pervoxel_lr_downrate=2,
    N_iters=10000,
)

fine_train = dict(
    N_iters=10000
)

Training images

002_masterchefcan_elev0_azim0

002_masterchefcan_elev22_azim0

Test renderings

Rendering the training poses works well, but the test poses have lots of distortion:

001 002 003

Coarse trained model

Viewing the coarse model, it looks like it is dense in a semi-spherical area around the can (essentially where all the cameras are pointing): image

Is this normal? Is it likely to be the problem? How can this be fixed?

Thanks!

sunset1995 commented 2 years ago

You should enable the background model or the background pixel will collapse to the foreground. Please see configs/nerf_unbounded/nerf_unbounded_default.py for more detail