GAE
Collection
Collection for GAE: Learning a Geometry-Native Latent Space for 3D-Consistent World Generation • 2 items • Updated • 1
Weights for GAE-64: a ~1B-parameter temporal DiT
(hidden_size=[768, 2048], depth=[28, 6]) over a 64-channel
geometry-native latent, at 672×378 and V=81, with metric Plücker
camera conditioning and Qwen3-0.6B text.
This repo is self-contained for GAE-64 inference: codec, per-channel latent
statistics, DA3 feature-level stats, and the flow transformer. The frozen
DA3-GIANT encoder / DPT head comes from
depth-anything/DA3-GIANT-1.1.
From the GAE code repository:
scripts/run_demo.sh
Or, after the files are in ckpts/:
python scripts/generate.py \
--image examples/scenes/forest_lake_trail.jpg \
--prompt-file examples/scenes/forest_lake_trail.txt \
--flow-ckpt ckpts/flow_gae64.pt \
--codec-ckpt ckpts/gae_64.pt \
--output results/forest
Image-to-video uses 50 Euler steps and CFG 2 with one reference view.
Layout:
codec/ — safetensors + config.jsongae_64.pt — drop-in checkpoint for gae.load_codeclatent_stats_gae_64.pt — per-channel latent mean/stdda3_stats_giant_5ds.tar — DA3 feature-level normalization statstransformer/ — flow safetensors + config.jsonflow_gae64.pt — drop-in checkpoint for gae.load_flow