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Fine Structure-Aware Sampling (FSS)

Official Implementation of "Fine Structure-Aware Sampling: A New Sampling Training Scheme for Pixel-Aligned Implicit Models in Single-View Human Reconstruction" accepted in AAAI 2024 (Main Track).

Prerequisite:

Refer to "environment_setup_for_FSS" text file to install the conda environment, get the required rendered RGB images, and generate the predicted normal maps.

Sample data:

We provided some sample data (i.e. Predicted Normal Maps and Sample points for 2 subjects from THuman2.0 dataset). Download from "https://drive.google.com/drive/folders/1QrcoeByfFdCNebHhWgxajdoZyjKBiUvt?usp=sharing" and make sure the downloaded folders are in the directory structure of: "FSS/trained_normal_maps" and "FSS/apps/results/stored_XXX".

To generate and store sample points using FSS.

conda activate fss cd ./FSS/apps
python generate_sample_pts_and_labels.py
The sample points will be saved in a folder under ./apps/results

To train the main model:

conda activate fss cd ./FSS/apps
python train_main.py Model weights and results will be saved in a folder under ./apps/checkpoints and ./apps/results respectively.