Closed egeozsoy closed 3 years ago
Sorry, we did not fully understand your question, and our method does not rely on point instance labels. Can you provide more information on your concerns?
Here https://github.com/zeliu98/Group-Free-3D/blob/ef8b7bb5c3bf5b49b957624595dc6a642b6d0036/scannet/scannet_detection_dataset.py#L74 you load the instance labels from scannet.
Here https://github.com/zeliu98/Group-Free-3D/blob/ef8b7bb5c3bf5b49b957624595dc6a642b6d0036/scannet/scannet_detection_dataset.py#L181 you use those instance labels to compute point_obj_mask and point_instance label.
And during the loss computation you use both the point_obj_mask https://github.com/zeliu98/Group-Free-3D/blob/ef8b7bb5c3bf5b49b957624595dc6a642b6d0036/models/loss_helper.py#L98 and the point_instance_label https://github.com/zeliu98/Group-Free-3D/blob/ef8b7bb5c3bf5b49b957624595dc6a642b6d0036/models/loss_helper.py#L25
How can the loss be computed without relying on the point instance labels?
Hi, this is used to assign a point to its' gt bbox.
votenet
: https://github.com/facebookresearch/votenet/blob/2f6d6d36ff98d96901182e935afe48ccee82d566/scannet/load_scannet_data.py#L125 here they prepared the _ins_label.npy
,
and used in: https://github.com/facebookresearch/votenet/blob/2f6d6d36ff98d96901182e935afe48ccee82d566/scannet/scannet_detection_dataset.py#L131-L138 to calculate the point_votes
and point_votes_mask
, which have the similar use with us. Besides, they comment that
# compute votes *AFTER* augmentation
# generate votes
# Note: since there's no map between bbox instance labels and
# pc instance_labels (it had been filtered
# in the data preparation step) we'll compute the instance bbox
# from the points sharing the same instance label.
Besides, you can refer to the preparation steps of SUNRGB for your need.
Is it possible to train the group-free network without having access to per point instance labels, so only using 3D bounding boxes? The loss calculation seems to depend on instance labels as far as I can tell