Comments (6)
For 6D object pose, we have released the code for PoseCNN, DeepIM, and PoseRBPF:
https://github.com/NVlabs/PoseCNN-PyTorch#training-and-testing-on-the-dexycb-dataset
https://github.com/NVlabs/DeepIM-PyTorch#training-and-testing-on-the-dexycb-dataset
https://github.com/NVlabs/PoseRBPF#testing-on-the-dexycb-dataset
As mentioned in the paper Sec. 5.3, we did not retrain PoseRBPF.
from dex-ycb-toolkit.
"I understood that the 3D models and poses annotation of the existing YCB and YCB (bop) is slightly different, am I correct?"
-> Correct.
Q1. Can you please clarify with regards to your dataset(ycbdex) pose annotation and 3d models related to bop dataset?? (ex, dexycb annotation follows the original YCB or YCB(bop))
-> We provide both.
- The original 6D pose annotation we provide in
pose.npz
(e.g., loaded in the dex-ycb-toolkit API, such as in this example) uses the YCB-Video models. If you download the DexYCB dataset, you can also find a copy of these models undermodels/
. - In addition, we also provide the 6D pose annotation using the YCB-V (BOP) models. This is stored under
bop/
. In fact,bop/
is a copy of the full DexYCB dataset under the BOP format, which you can directly use with any methods that consume this format, e.g. CosyPose. If you look atbop/models/
andbop/models_eval/
, you'll find that these models are directly copied from YCB-V (BOP).
Q2. I want to check performance on dexycb dataset using pretrained CosyPose or PoseCNN trained from YCB or YCB(bop) without training dexycb dataset. Have you already tried this?? If yes, Can you share the results?? It would be really helpful.
-> We don't have pre-trained results. It should be possible to get that for PoseCNN using their released repo. You need to regenerate the results with the pre-trained model and then run eval (see here).
Q3. Is there any reason a large clamp was removed compared to the YCB dataset??
-> We did not include 051_large_clamp
since it it sufficiently similar to 052_extra_large_clamp
.
from dex-ycb-toolkit.
No, there is no plan for that.
from dex-ycb-toolkit.
I am curious if there is any plan to provide training codes related to other estimations (2D detection, 6d object pose estimation).
from dex-ycb-toolkit.
I have some simple question about the dataset and toolkit!
I observed your toolkit used the bop toolkit and I observed something in bop datasets.
They mentioned that the ground-truth poses are transformed by converted 3D models.
I understood that the 3D models and poses annotation of the existing YCB and YCB (bop) is slightly different, am I correct?
Q1. Can you please clarify with regards to your dataset(ycbdex) pose annotation and 3d models related to bop dataset?? (ex, dexycb annotation follows the original YCB or YCB(bop))
Q2. I want to check performance on dexycb dataset using pretrained CosyPose or PoseCNN trained from YCB or YCB(bop) without training dexycb dataset. Have you already tried this?? If yes, Can you share the results?? It would be really helpful.
Q3. Is there any reason a large clamp was removed compared to the YCB dataset??
from dex-ycb-toolkit.
Thanks for the detailed reply!
from dex-ycb-toolkit.
Related Issues (20)
- How to use this dataset HOT 4
- hand pose, translatation and rotation parameters HOT 2
- the form of hand pose annotations HOT 8
- Trained weights of Mask R-CNN and SOLOv2
- Depth ambiguity for RGB only methods HOT 1
- Inconsistency in pose_y for per_image and per_sequence HOT 7
- How to obtain point cloud of object? HOT 1
- mano shape consistency for right and left hand. HOT 4
- Objects in the DEXYCB dataset HOT 1
- Does the dataset provide 3D object bbox? HOT 4
- ModuleNotFoundError: No module named 'utils.eval_util' while testing examples/evaluate_hpe.py HOT 2
- MANO pose coefficients (theta) HOT 5
- subject-specific hand shapes (ß) HOT 2
- World Frame Alignment HOT 1
- One more videos for class 2. HOT 1
- Question on teaser HOT 1
- pyglet 2.0.9 requires Python 3.8 or newer. HOT 2
- How to get absolute depth values for each pixel? HOT 3
- Banana point cloud looks flattened HOT 2
- Why y-axis and z-axis multiply by -1? HOT 2
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