This hosts the benchmarking instructions and leaderboard of SQA3D.
- We've moved! This is the new benchmark and leaderboard site of SQA3D.
Please send your result to [email protected]. With the following information:
-
The task of your submission. We hosted two tracks for now (you may find more information on our challenge website):
-
Your setting. Feel free to elaborate a bit on your model:
- The scene context you use:
3D
(point cloud),video
,BEV
picture. - (QA only): Whether the model uses ground truth location and orientation.
- The scene context you use:
-
The name of your model (or team).
-
Result. Metrics can be found at here (localization) and here (QA).
Rank | Model | [email protected] |
[email protected] |
Acc@15° |
Acc@30° |
Information |
---|---|---|---|---|---|---|
1 | PKU_WICT_2023 | 33.50% | 70.35% | 72.74% | 76.77% | details |
2 | Tsinghua_AIR_2023 | 34.41% | 55.27% | 40.07% | 44.98% | |
3 | Random | 14.60 | 34.21 | 22.39 | 42.28 |
Rank | Model | scene context | ground truth situation | Acc (top-1) |
Information |
---|---|---|---|---|---|
- | Human | 3D | 90.06 | ||
1 | PKU_WICT_2023 | 3D + video | 54.02 | details | |
2 | ScanQA | 3D | ✔️ | 47.2 | |
3 | ScanQA | 3D | 46.58 | ||
4 | MCAN | BEV | 43.42 | ||
5 | ClipBERT | video | 43.31 | ||
6 | GPT-3+ScanRefer | 3D | 41.00 |