CVMI-Lab / DODA

(ECCV 2022) DODA: Data-oriented Sim-to-Real Domain Adaptation for 3D Semantic Segmentation
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What is the difference between DODA(Only VSS) and DODA (w/o TACM ) #7

Open xiaodongww opened 1 year ago

xiaodongww commented 1 year ago

Hi, thanks for your work. I have a small question on Table 1 of your paper.

You reported three results DODA (only VSS), DODA(w/oTACM), DODA. From my understanding, there are two modules VSS and TACM, then what is the difference between DODA(Only VSS) andDODA (w/o TACM )? Do I miss something else?

Thanks!

Dingry commented 1 year ago

Hi, DODA (only VSS) means the model is pretrained with VSS without self-training. DODA (w/o TACM) means the model is pretrained with VSS and self-trained without TACM.

xiaodongww commented 1 year ago

Thanks for your quick reply! @Dingry Here is another question. Is the self-training strategy orthogonal to existing UDA methods like MCD or MMD? Will the performance of DODA be further improved if we apply MMD loss on backbone feature learning?

Dingry commented 1 year ago

Hi, I think they are orthogonal, since TACM is applied at the data level. But I haven't tried MCD or MMD with TACM. You can try it if you are interested and looking forward to your results!

xiaodongww commented 1 year ago

Thanks for your reply very much. Do you have a plan for when to release the code of the baseline UDA methods? I tried to implement MCD for domain adaptation by myself but found the training process corrupted.

Dingry commented 1 year ago

Hi, thanks for your attention. We have plan to release baseline methods but don't have exact time now since we are working with another paper. We will try to re-organize code and release it later. Thanks!