GLD: Geometric Latent Diffusion

Repurposing Geometric Foundation Models for Multi-view Diffusion

[Project Page] | [Code]

Quick Start

git clone https://github.com/cvlab-kaist/GLD.git
cd GLD
conda env create -f environment.yml
conda activate gld

# Download all checkpoints
python -c "from huggingface_hub import snapshot_download; snapshot_download('SeonghuJeon/GLD', local_dir='.')"

# Run demo
./run_demo.sh da3

Files

File	Description	Params	Size
checkpoints/da3_level1.pt	DA3 Level-1 diffusion (EMA)	783M	2.9G
checkpoints/da3_cascade.pt	DA3 Cascade: L1→L0 (EMA)	473M	1.8G
checkpoints/vggt_level1.pt	VGGT Level-1 diffusion (EMA)	806M	3.0G
checkpoints/vggt_cascade.pt	VGGT Cascade: L1→L0 (EMA)	806M	3.0G
pretrained_models/da3/model.safetensors	DA3-Base encoder	135M	0.5G
pretrained_models/da3/dpt_decoder.pt	DPT decoder (depth + geometry)	-	1.1G
pretrained_models/mae_decoder.pt	DA3 MAE decoder (EMA, decoder-only)	423M	1.6G
pretrained_models/vggt/mae_decoder.pt	VGGT MAE decoder (EMA, decoder-only)	425M	1.6G

Stage-2 and MAE decoder checkpoints contain EMA weights only. MAE decoder checkpoints contain decoder weights only (encoder removed).