🔍 Challenge overview
The Grounded CoMPaT Recognition (GCR) is a compositional 3D vision task that aims to collectively recognize and ground compositions of materials on parts of 3D objects. This task is based on the 3DCoMPaT dataset++, a large-scale dataset composed of stylized 3D objects and associated 2D renderings. We propose two variations of this task: GCR-Coarse and GCR-Fine, which are based on coarse-grained and fine-grained 3D segmentations of the 3DCoMPaT models. We highly encourage participants of the challenge to enter and submit to both tracks of the challenge.📊 Dataset
The 3DCoMPaT dataset++ for both challenge tracks is available through our download page.📨 Submission
Submission will be made through the eval.ai platform.📜 Rules
Here are the rules for the challenge:- Submission Limit: Each participant is allowed to submit their solution a maximum of three times per day.
- Data Usage: Participants are not permitted to use any data other than the 3DCoMPaT data for training their models.
- Technical Report: Each participant must submit a technical report detailing their methods, which will be made public, in order to be eligible for any prizes or rewards.
🏆 Awards
Total prize pool: TBD. Teams are encouraged to particpate to both challenge tracks.Fine track:
- 1st: TBD
- 2nd: TBD
Coarse track:
- 1st: TBD
- 2nd: TBD
💬 Q&A
If you encounter any technical issue related to the challenge, or if you're missing critical information, please open a ticket on our GitHub repository.🎉 2023 Winning Solution
We share below the previous year's solution winner, and her winning solution repository below: