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License: Apache License 2.0
DeVIS: Making Deformable Transformers Work for Video Instance Segmentation
License: Apache License 2.0
Hello, I'm trying to train DeVIS with custom data. (Which contains only 1 class, i.e. a MOT like dataset)
I observe that the output mask for each instance track contains the segmentation mask for all instances inside the frame instead of just one. (I was expecting each query would give a single instance-level segmentation instead of per-class or per-frame segmentation)
Is this an expected behavior??
If you have experienced this before, any kind of advice would be appreciated!
Also, will the model checkpoints become available at any point?
Hello, Thanks for your great work! I would like to ask the attention computation in class TemporalMSDeformAttnEncoder.
in 473 lines, temporal_ref_points = reference_points[t, :, 0][None, :, None, None, None]
why not use multi-scale reference points, like TemporalMSDeformAttnDncoder?
temporal_ref_points = reference_points[t].repeat(1, self.t_window, 1)[None, :,None, :, None]
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