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CredSplatting: Perception Credence Oriented Feed-forward 3D Gaussian Splatting from Scalable Views

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🚀Datasets

Download DTU data and Depth raw. Unzip and organize them as:

yours_datasets_path
    ├── dtu                   
        ├── Cameras                
        ├── Depths   
        ├── Depths_raw
        └── Rectified

Download Real Forward-facing, and Tanks and Temples datasets. Then modify the dataset path in the YAML files under the configs folder.

🚀Evaluation

Evaluation on DTU

torchrun --nproc_per_node=1 --master_port=29501 run.py --type evaluate --cfg_file configs/credsplatting/dtu_pretrain.yaml credsplatting.cas_config.render_if True,True credsplatting.cas_config.volume_planes 64,8 credsplatting.eval_depth True gpus 0, 

Evaluation on Real Forward-facing

torchrun --nproc_per_node=1  --master_port=29500 run.py --type evaluate --cfg_file configs/credsplatting/llff_eval.yaml distributed True gpus 0, credsplatting.cas_config.render_if False,True

Evaluation on Tanks and Temples datasets

torchrun --nproc_per_node=1  --master_port=29500 run.py --type evaluate --cfg_file configs/credsplatting/tnt_eval.yaml distributed True gpus 0, credsplatting.cas_config.render_if False,True

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CredSplatting: Perception Credence Oriented Feed-forward 3D Gaussian Splatting from Scalable Views

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