Helpful links: [Project Page] [PDF] [ArXiv] [Demo]

To run this code, clone and install via:

git clone COBL_PUBLIC_PATH ./install.sh 

You may need to edit the torch and xformers settings in the install file to match your own CUDA version. This default file uses CUDA 12.6 and Pytorch 2.7.1, Python 3.10.13

You can access the Tabletop dataset containing synthetic (train) and real-world (test) scenes by:

(1) Cloning and installing this github repository, then calling:

from cobl.Tabletop import Tabletop test_dat = Tabletop(split=SPLIT) # SPLIT = "test" or "train" 

(2) or without downloading this CoBL Repository, by loading from Huggingface Datasets:

from datasets import load_dataset cobl = load_dataset("DeanHazineh1/CoBL_Tabletop") sample = cobl[SPLIT][0] # SPLIT = "test" or "train" 

If you find this repo useful, please consider citing:

@article{damaraju2025cobl, author={Damaraju, Aneel and Hazineh, Dean and Zickler, Todd}, title={CObL: Toward Zero-Shot Ordinal Layering without User Prompting}, journal={ICCV}, year={2025}, }