Comments (3)
There are two cases I can think of. For one, if the target is occluded by some other objects/background, the reconstructed shape will be (mistakenly) penalized by the silhouette reconstruction loss due to the wrong off-the-shelf segmentations. In this case, banmo would likely fail.
In the second case, if the object is out of the image boundary, banmo should work, since out-of-frame pixels are not sampled to compute losses. However in practice, this may still produce worse results since off-the-shelf segmentation method is usually not robust to partially out-of-frame objects.
from banmo.
Hi, based on the results on a few categories we tried (e.g., penguin, laikago robot, eagle, hands, results on this page), densepose is not that important given good enough initial root pose.
Also note those cases do not contain challenging self-occlusions caused by articulations. I think some form of correspondence like densepose-cse is still needed for more challenging cases.
from banmo.
Thanks for the quick response!
One last question: How well does the method perform when part of the video contains heavy occlusion? For example, you have a lot of frames in which the object is occluded a little but in some frames the object is heavily occluded. I am curious in how the method handles occlusion in those heavily occluded frames.
from banmo.
Related Issues (20)
- Could you provide a demo that can work with one-click HOT 1
- Running out of space when running AMA (Samba + Swing) HOT 2
- Questions about the code. HOT 2
- Mesh generated on AMA-swing and Eval code HOT 2
- About projecting 3D verteces to 2D images HOT 1
- Error when rendering AMA-swing dataset HOT 2
- unable to load materials from: ./wood.obj.mtl HOT 3
- nvs_iter.sh HOT 2
- Extracting root pose HOT 1
- Loading the ".npy" files such as "cat-pikachiu.npy" or "shiba-haru-1.npy" has been failed HOT 3
- Questions about output results HOT 8
- exporting 3D models with skinning HOT 5
- Can Banmo support torch 1.11+cu113? HOT 1
- BANMo VS. ViSER HOT 2
- Clarification of the Matching Loss HOT 3
- Ckpt Release HOT 1
- face_normals all zero,ignoring
- The problem of extracting masks for deformable dynamic target objects HOT 3
- Enhancing Mesh Quality and Texture in BANMo Extracted Models HOT 1
- Questions about PoseNet HOT 4
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from banmo.