superquadric_parsing
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Code for "Superquadrics Revisited: Learning 3D Shape Parsing beyond Cuboids", CVPR 2019
Hello there! Thanks a lot for your amazing work! I was just using your repo which is being used in [Learnable Earthparser](https://github.com/romainloiseau/LearnableEarthParser). I found that the PyTorch version required by...
Hi, Thanks for the great work! I have an inquiry related to overlapping loss [here](https://github.com/paschalidoud/superquadric_parsing/blob/19e365f012fb34c5997d2d5c28a5c121228d8063/learnable_primitives/regularizers.py#L57). Why is "the measure of primitive that are inside other primitives" defined as "points whose...
Hello, This work is great! I was wondering if there is a way to extend this work to support estimation of superquadrics using an RGBD image only, say from a...
Hi, @paschalidoud , I try to train the model by Running a command : python scripts/train_network.py ../../03001627_simple_chair/ tmp/ --epochs 50000 --use_sq --lr 1e-4 --n_primitives 20 --architecture tulsiani --dataset_type shapenet_v2 --use_chamfer...
hi, thanks you for share such great work! May I ask if I want to reproduce the result in table 1, which regularizers should I choose and what are its...
Hi I am very interested in your work and I'm trying to retrain the chair parsing network. But after following all the instructions as README and using same arguments, my...
Interesting work! I'm wondering if you can please provide the weight files for the trained model in you paper. Also, instructions on how to prepare the data for training/evaluation would...
Thank you for your work! However, while I was trying to run your evaluation code, I came across with an issue when compiling the sampler files and here is the...
Bumps [torch](https://github.com/pytorch/pytorch) from 0.4.1 to 2.2.0. Release notes Sourced from torch's releases. PyTorch 2.2: FlashAttention-v2, AOTInductor PyTorch 2.2 Release Notes Highlights Backwards Incompatible Changes Deprecations New Features Improvements Bug fixes...