VGGT-Diff NVS 480x832
This is the full-resolution independent-view checkpoint used for VGGT-Diff's quantitative comparison with other novel-view synthesis baselines. It is the paper's controlled clean-1K setting, with 980 available training scenes.
Configuration
- Resolution: 480 x 832
- Task: independent-view novel-view synthesis
- Input: six posed source views and target cameras
- VAE: source and target views are encoded independently
- Geometry: frozen VGGT-Omega features with camera conditioning
- Training data: DL3DV clean-1K (980 available scenes)
- Training schedule: 147 epochs at 192 x 336 (approximately 18K optimizer steps), followed by 60 epochs at 480 x 832
- Full-resolution continuation: 7,380 optimizer steps
- Intended use: the full-resolution NVS setting used for baseline comparison
For a controlled comparison, the paper follows the data scale and optimization budget of the FrameCrafter setting. The released checkpoint reflects that fixed comparison budget rather than a fully saturated endpoint. The full-resolution training curve did not show a clear convergence plateau, so continued optimization is expected to improve performance further.
The paper's 6-to-1 evaluation used 50 diffusion steps and target-only early Omega CFG with scale 2.0.
Usage
python scripts/infer.py \
--training-mode nvs \
--checkpoint /path/to/vggt-diff.safetensors \
--omega-checkpoint /path/to/vggt_omega_1b_512.pt \
--height 480 --width 832
VGGT-Omega weights and Wan2.1 base-model files are separate dependencies and are not redistributed in this repository.
Links
License
Released under the non-commercial VGGT-Diff Research License. Third-party models and datasets remain subject to their own terms.