GeoNVS / README.md
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Use the paper terminology for the fusion variants
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---
license: other
license_name: stabilityai-ai-non-commercial
license_link: https://huggingface.co/stabilityai/stable-virtual-camera/blob/main/LICENSE
base_model: stabilityai/stable-virtual-camera
pipeline_tag: image-to-video
tags:
- novel-view-synthesis
- video-diffusion
- 3d-gaussian-splatting
---
# GeoNVS: Geometry Grounded Video Diffusion for Novel View Synthesis
GS-Adapter and LoRA weights for **GeoNVS**, which injects explicit 3D Gaussian
geometry into camera-controlled video diffusion models.
[Project page](https://sites.google.com/view/minjun-kang/geonvs-eccv26)  | 
[Paper](https://arxiv.org/abs/2603.14965)  | 
[Code](https://github.com/MinJunKang/GeoNVS)
These weights are fine-tuned from
[`stabilityai/stable-virtual-camera`](https://huggingface.co/stabilityai/stable-virtual-camera)
(SEVA) and [CameraCtrl](https://github.com/hehao13/CameraCtrl) (SVD backbone),
and **inherit the Stability AI Non-Commercial Research Community License**
using them requires the base models and acceptance of their licenses.
Non-commercial research use only.
## Files
| Path | Backbone | Description |
|---|---|---|
| `eccv_gattn/` | SEVA | Main GeoNVS model, Adaptive Fusion (`fusion_method: gattn`): `gs_adapter_weights.pth` + `pytorch_lora_weights.safetensors` |
| `eccv_camctrl/` | CameraCtrl (SVD) | GeoNVS on CameraCtrl: adapter + LoRA |
| `eccv_base/` | SEVA | Fusion ablation: Naive Fusion (`fusion_method: concat`), use with `configs/module_config/gsadapter_eccv_base.yaml` |
## Usage
Use with the [GeoNVS code release](https://github.com/MinJunKang/GeoNVS) —
`tools/scripts/download_weights_ours.sh` fetches these files into
`pretrained_weights/`, then:
```bash
python demo.py --data_path <benchmarkset>/dl3dv10 --num_inputs 3 \
--gs_adapter_config configs/module_config/gsadapter_eccv_gattn.yaml \
--gs_adapter_weight_path pretrained_weights/eccv_gattn \
--lrm_model_name vggt_iv --H=384 --W=384 --version=1.0
```
## Mirrored third-party checkpoint
`third_party/depthsplat-gs-base-re10kdl3dv-448x768-randview2-6-f40abc4f.pth` is
redistributed from [DepthSplat](https://github.com/cvg/depthsplat)
(MIT License, © 2024 Haofei Xu). It is the checkpoint used for the paper's
experiments; upstream has since replaced it with a retrained file
(`f8ddd845`) that measurably changes results, so the original is mirrored here
for reproducibility. Its MIT license governs that file.