| --- |
| tags: |
| - gaussian-splatting |
| - novel-view-synthesis |
| - dynamic-scene-reconstruction |
| - pytorch |
| --- |
| |
| # Mango-GS Weights |
|
|
| Pretrained inference weights for |
| [Mango-GS](https://github.com/htx0601/Mango-GS). See the |
| [paper](https://arxiv.org/abs/2603.11543) for the method and evaluation |
| protocol. |
|
|
| ## Download |
|
|
| Download the repository directly into the public code's `weights/` folder: |
|
|
| ```bash |
| hf download htx0601/Mango-GS --local-dir weights |
| ``` |
|
|
| Each scene directory contains `cfg_args`, `point_cloud.ply`, and `deform.pth`. |
| The release scripts load these files directly without a checkpoint argument. |
|
|
| ## Inference Parameters |
|
|
| | Dataset | Scenes | T | K | Nodes | Resolution | |
| |---|---|---:|---:|---:|---:| |
| | N3V | coffee_martini, flame_salmon_1 | 4 | 3 | 2048 | 2 | |
| | N3V | cook_spinach, cut_roasted_beef, flame_steak, sear_steak | 4 | 5 | 4096 | 2 | |
| | HyperNeRF | broom2, vrig-3dprinter, vrig-chicken | 6 | 3 | 2048 | 2 | |
| | HyperNeRF | vrig-peel-banana | 8 | 3 | 4096 | 2 | |
|
|
| The same machine-readable parameters are provided in `manifest.json` and in |
| each scene's `cfg_args`. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{huang2026mangogs, |
| title = {Mango-GS: Enhancing Spatio-Temporal Consistency in Dynamic Scenes Reconstruction using Multi-Frame Node-Guided 4D Gaussian Splatting}, |
| author = {Huang, Tingxuan and Zhu, Haowei and Yong, Jun-hai and Pan, Hao and Wang, Bin}, |
| booktitle = {International Conference on Learning Representations}, |
| year = {2026} |
| } |
| ``` |
|
|
