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README.md

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----
-license: mit
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+---
+license: mit
+base_model:
+- stabilityai/stable-diffusion-2
+---
+# StableMotion: Repurposing Diffusion-Based Image Priors for Motion Estimation
+This is the official repo for paper [StableMotion: Repurposing Diffusion-Based Image Priors for Motion Estimation](https://www.arxiv.org/abs/2505.06668)
+
+## Setup
+0. Clone the [code repo](https://github.com/ziyiwhat/StableMotion).
+1. Create your environment from `requirements.txt`.
+2. Download [DIR-D](https://drive.google.com/file/d/1KR5DtekPJin3bmQPlTGP4wbM1zFR80ak/view?usp=sharing) and [RS-Real](https://huggingface.co/datasets/Yzl-code/RS-Diffusion/tree/main). Put them into `StableMotion_SIR` and `StableMotion_RSC` respectively.
+
+## StableMotion for Stitched Image Rectangling (SIR)
+### Inference
+0. Download the checkpoints of "StableMotion_SIR"
+1. Run "cd StableMotion_SIR && sh sample.sh". You may want to change this file to modify the inference configurations.
+2. Run "sh metrics.sh" to evaluate the results.
+
+### Training
+0. Replicate [RecDiffusion](https://github.com/lhaippp/RecDiffusion) to get pseudo labels, i.e., the flow labels generated by [RecDiffusion](https://github.com/lhaippp/RecDiffusion) on the training set of [DIR-D](https://drive.google.com/file/d/1KR5DtekPJin3bmQPlTGP4wbM1zFR80ak/view?usp=sharing). Put and rename it into `StableMotion_SIR/MDM_Flow`.
+1. Run "cd StableMotion_SIR && sh train.sh". You may want to change this file to modify the training configurations. The default configuration requires approximately 80 GB of VRAM per card.
+
+## StableMotion for Rolling Shutter Correction (RSC)
+### Inference
+0. Download the checkpoints of "StableMotion_RSC"
+1. Run "cd StableMotion_RSC && sh sample.sh". You may want to change this file to modify the inference configurations.
+2. Run "sh metrics.sh" to evaluate the results.
+
+### Training
+Run "cd StableMotion_RSC && sh train.sh". You may want to change this file to modify the training configurations. The default configuration requires approximately 40 GB of VRAM per card.