zeliu98 / Group-Free-3D

Group-Free 3D Object Detection via Transformers
MIT License
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Training without Instance Segmentation #14

Closed egeozsoy closed 3 years ago

egeozsoy commented 3 years ago

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

stupidZZ commented 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?

egeozsoy commented 3 years ago

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?

zeliu98 commented 3 years ago

Hi, this is used to assign a point to its' gt bbox.

Besides, you can refer to the preparation steps of SUNRGB for your need.