DA-MVSNet

⚙ Setup

1. Recommended environment

• PyTorch 1.12
• Python 3.8

2. DTU Dataset

Training Data. We adopt the full resolution ground-truth depth provided in CasMVSNet or MVSNet. Download DTU training data and Depth raw. Unzip them and put the Depth_raw to dtu_training folder. The structure is just like:

dtu_training                          
       ├── Cameras                
       ├── Depths   
       ├── Depths_raw
       └── Rectified

Testing Data. Download DTU testing data and unzip it. The structure is just like:

dtu_testing                          
       ├── Cameras                
       ├── scan1   
       ├── scan2
       ├── ...

3. BlendedMVS Dataset

Training Data and Validation Data. Download BlendedMVS and unzip it. And we only adopt BlendedMVS for finetuning and not testing on it. The structure is just like:

blendedmvs                          
       ├── 5a0271884e62597cdee0d0eb                
       ├── 5a3ca9cb270f0e3f14d0eddb   
       ├── ...
       ├── training_list.txt
       ├── ...

4. Tanks and Temples Dataset

Testing Data. Download Tanks and Temples and unzip it. Here, we adopt the camera parameters of short depth range version (Included in your download), therefore, you should replace the cams folder in intermediate folder with the short depth range version manually. The structure is just like:

tanksandtemples                          
       ├── advanced                 
       │   ├── Auditorium       
       │   ├── ...  
       └── intermediate
           ├── Family       
           ├── ...          

📊 Testing

1. DTU testing

Fusibile installation. Since we adopt Gipuma to filter and fuse the point on DTU dataset, you need to install Fusibile first. Download fusible to <your fusibile path> and execute the following commands:

cd <your fusibile path>
cmake .
make

Point generation. To recreate the results from our paper, you need to specify the datapath to <your dtu_testing path>, outdir to <your output save path>, resume to <your model path>, and fusibile_exe_path to <your fusibile path>/fusibile in shell file ./script/test.sh first and then run:

bash ./scripts/test.sh

2. Tanks and Temples testing

Point generation. Similarly, you need specify the datapath, outdir and resume in shell file ./scripts/test_tnt.sh, and then run:

bash ./scripts/test_tnt.sh

⏳ Training

1. DTU training

To train the model from scratch on DTU, specify the datapath and log_dir in ./scripts/train.sh first and then run:

bash ./scripts/train.sh

2. BlendedMVS fine-tuning

To fine-tune the model on BlendedMVS, you need specify datapath, log_dir and resume in ./scripts/blendedmvs_finetune.sh first, then run:

bash ./scripts/blendedmvs_finetune.sh