Layout-based Causal Inference for Object Navigation Setup Clone the repository and move into the top-level directory cd Layout-based-sTDE Create conda environment. conda env create -f environment.yml Activate the environment. conda activate ng We provide pre-trained model of ORG+L-sTDE. Please download and put it in the ./trained_models folder. Our settings of dataset follows previous works, please refer to HOZ for AI2THOR and SemExp for Gibson. Training and Evaluation Train our Layout-based model python main.py \ --title layoutmodel \ --model LayoutModel \ --workers 12 \ --gpu-ids 0 Evaluate our model with sTDE (our Layout-based sTDE model) python full_eval.py \ --title layoutmodel \ --model LayoutModel \ --results-json layoutmodel_sTDE.json \ --gpu-ids 0 \ --TDE_self True \ --TDE_threshold 0.5 \ --TDE_mode zero