Open chanhee-luke opened 3 months ago
You can also see in the paper's statistics that we take the 288 categories with the most objects (>10 instances per category) for the detection benchmark. The remaining categories have much fewer objects and form the long-tailed distribution. We may consider releasing all of them for potential usage of these annotations if you think they are valuable for your research. Looking forward to more feedback about this issue.
Hi Tai, it was nice talking to you in CVPR!
I hope you will consider releasing the full annotations, as having a long-tailed distribution is closer to real-life scenarios where this dataset will be most beneficial. I am mainly working on long-horizon task planning, and having comprehensive coverage of objects is important for my research interests. Thank you!
Hi Luke, glad to see you coming to try our dataset and repo!
Thanks for your suggestion, and we will consider releasing the full annotation with long-tailed categories in the next update. We will try to release the new ARKitScenes' annotations and MMScan's language annotations together with your mentioned modification in about one month.
Please, Xiaohan@mxh1999, have a look at this issue and remember this issue during the update.
Appreciate the quick response! I'll be looking forward to those :)
Branch
main branch https://mmdetection3d.readthedocs.io/en/latest/
📚 The doc issue
Hi! Thanks for the awesome work and the extensive annotations! :)
I have a question about the number of categories. I read in the paper that the total number of categories is over 760, but I only see 288 categories in the .pkl files for both train and validation. I assume that's why some objects have bounding boxes but are labeled as "object"? Are you planning to release annotations for more categories, or is this all?
Thanks!
-Luke
Suggest a potential alternative/fix
No response