Update README.md

README.md

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----
-license: creativeml-openrail-m
----
+---
+license: creativeml-openrail-m
+---
+---
+language:
+- en
+license: apache-2.0
+tags:
+- depth estimation
+- panoramic images
+- high resolution
+- image analysis
+- computer vision
+- in-the-wild
+- zero-shot
+---
+
+<h1 align="center">PaGeR(Panoramic Geometry Estimation) depth estimation Model Card</h1>
+
+<p align="center">
+<a title="Github" href="https://github.com/prs-eth/marigold" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/github/stars/prs-eth/marigold?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="Github">
+</a>
+<a title="Website" href="https://marigoldcomputervision.github.io/" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/badge/%E2%99%A5%20Project%20-Website-blue" alt="Website">
+</a>
+<a title="arXiv" href="https://arxiv.org/abs/2505.09358" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/badge/%F0%9F%93%84%20Read%20-Paper-AF3436" alt="arXiv">
+</a>
+<a title="Social" href="https://twitter.com/antonobukhov1" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/twitter/follow/:?label=Subscribe%20for%20updates!" alt="Social">
+</a>
+<a title="License" href="https://www.apache.org/licenses/LICENSE-2.0" target="_blank" rel="noopener noreferrer" style="display: inline-block;">
+    <img src="https://img.shields.io/badge/License-Apache--2.0-929292" alt="License">
+</a>
+</p>
+
+This is a model card for the `PaGeR-depth` model for monocular depth estimation from a single panoramic [ERP](https://en.wikipedia.org/wiki/Equirectangular_projection) image. 
+The model is fine-tuned from the `marigold-e2e-ft` [model](https://huggingface.co/GonzaloMG/marigold-e2e-ft-depth) as 
+described in our paper:
+- [CVPR'2026 paper(hopefully)](paper link) titled "Panorama Geometry Estimation using Single-Step Diffusion Models"
+
+## Model Details
+- **Developed by:** [Vukasin Bozic](http://www.kebingxin.com/), [Kevin Qu](https://ch.linkedin.com/in/kevin-qu-b3417621b), [Tianfu Wang](https://tianfwang.github.io/), [Nando Metzger](https://nandometzger.github.io/), [Shengyu Huang](https://shengyuh.github.io/), [Bo Li](https://www.linkedin.com/in/bobboli0202), [Anton Obukhov](https://www.obukhov.ai/), [Konrad Schindler](https://scholar.google.com/citations?user=FZuNgqIAAAAJ).
+- **Model type:** Generative latent diffusion-based one-step scale-invariant and metric monocular panoramic depth estimation from a single ERP image.
+- **Language:** English.
+- **License:** [Apache License License Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).
+- **Model Description:** This model can be used to generate an estimated depth map of a panoramic input image. 
+  - **Resolution**: The model is designed to support large resolutions up to 3K.
+  - **Steps and scheduler**: This model works in a swift, one-step regime.
+  - **Outputs**:
+    - **Scale-invariant depth map**: The predicted values represent a depth map, interpolating between the near and far planes of the model's choice.
+- **Resources for more information:** [Project Website](insert link), [Paper](insert link), [Code](https://github.com/prs-eth/PaGeR).
+- **Cite as:**
+
+```bibtex
+Add citation
+```