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license: apache-2.0
library_name: pytorch
tags:
- depth-estimation
- 3d-reconstruction
- multi-view
- camera-pose
- gaussian-splatting
- depth-anything-3
- vggt
pipeline_tag: depth-estimation
---
# MDA — Multi-view depth & geometry checkpoints
These are the official model checkpoints for the paper
**"Modeling Depth Ambiguity: A Mixture-Density Representation for Flying-Point-Free Depth Estimation"** (MDA).
📄 [arXiv](https://arxiv.org/abs/2606.02552) | 🌐 [Project page](https://biansy000.github.io/mda-site/)
MDA is a mixture-density depth representation that predicts several depth
hypotheses (with their probabilities) at every pixel instead of forcing a single
depth, which largely removes the *flying-point* artifacts at object boundaries
that plague feed-forward depth estimators. See the [Citation](#citation) section
to cite this work.
These two checkpoints are used for multi-view geometry prediction —
spatially consistent depth and camera pose from a set of input images. They are
built on two different backbones and trained with a Mixture-of-Gaussians (MoG)
depth head and a `logl2` objective.
| File | Backbone | Wrapper | `model_choice.py` name | Params |
|---|---|---|---|---|
| [`DA3_MOG_Sky_LogL2.ckpt`](./DA3_MOG_Sky_LogL2.ckpt) | DA3 Giant | `DA3Wrapper` | `mda_mog_sky_l2` | ~1.36 B |
| [`VGGT_MOG_LogL2.ckpt`](./VGGT_MOG_LogL2.ckpt) | VGGT-1B | `VGGTWrapper` | `vggt_mog_l2` | ~1.16 B |
Both are PyTorch Lightning checkpoints (`save_weights_only=True`, Lightning 2.5.6).
State-dict keys are prefixed `net.net.*` because the network is wrapped by a
Lightning module — strip the prefix and load into the bare net. These are **research checkpoints** and are **not** loadable
through the standard `DepthAnything3.from_pretrained` HF API.
## Citation
If you build on **MDA**, please cite:
```bibtex
@misc{bian2026modeling,
title = {Modeling Depth Ambiguity: A Mixture-Density Representation for Flying-Point-Free Depth Estimation},
author = {Siyuan Bian and Congrong Xu and Jun Gao},
year = {2026},
eprint = {2606.02552},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/2606.02552}
}
```
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