Enhance OpenDWM dataset card: Add metadata, links, and usage example for CVD-STORM

README.md

@@ -1,5 +1,60 @@
----
-license: apache-2.0
----
-
-Data packages used by the OpenDWM project.
+---
+license: apache-2.0
+task_categories:
+- text-to-video
+- text-to-3d
+language: en
+tags:
+- autonomous-driving
+- world-model
+---
+
+# OpenDWM Dataset
+
+This repository contains data packages used by the [Open Driving World Models (OpenDWM)](https://github.com/SenseTime-FVG/OpenDWM) project. The OpenDWM project is an open-source initiative focused on autonomous driving video generation.
+
+The data packages support the development of generative models for world modeling, environment simulation, and future state prediction in autonomous driving. They are utilized in research such as the paper [CVD-STORM: Cross-View Video Diffusion with Spatial-Temporal Reconstruction Model for Autonomous Driving](https://huggingface.co/papers/2510.07944), which proposes a cross-view video diffusion model leveraging a spatial-temporal reconstruction VAE to generate long-term, multi-view videos with 4D reconstruction capabilities under various control inputs.
+
+-   **Paper**: [CVD-STORM: Cross-View Video Diffusion with Spatial-Temporal Reconstruction Model for Autonomous Driving](https://huggingface.co/papers/2510.07944)
+-   **Project Page**: https://sensetime-fvg.github.io/CVD-STORM/
+-   **Code**: https://github.com/SenseTime-FVG/OpenDWM
+
+## Sample Usage
+
+To get started with OpenDWM and utilize these data packages for generation, follow the setup instructions and then use the provided example code for video generation.
+
+### Setup
+
+Hardware requirement:
+
+*   Training and testing multi-view image generation or short video (<= 6 frames per iteration) generation requires 32GB GPU memory (e.g. V100)
+*   Training and testing multi-view long video (6 ~ 40 frames per iteration) generation requires 80GB GPU memory (e.g. A100, H100)
+
+Software requirement:
+
+*   git (>= 2.25)
+*   python (>= 3.9)
+
+Install the [PyTorch](https://pytorch.org/) >= 2.5:
+
+```bash
+python -m pip install torch==2.5.1 torchvision==0.20.1
+```
+
+Clone the repository, then install the dependencies.
+
+```bash
+cd OpenDWM
+git submodule update --init --recursive
+python -m pip install -r requirements.txt
+```
+
+### T2I, T2V generation with CTSD pipeline
+
+Download base model (for VAE, text encoders, scheduler config) and driving generation model checkpoint, and edit the [path](https://github.com/SenseTime-FVG/OpenDWM/blob/main/examples/ctsd_35_6views_image_generation.json#L102) and [prompts](https://github.com/SenseTime-FVG/OpenDWM/blob/main/examples/ctsd_35_6views_image_generation.json#L221) in the JSON config, then run this command.
+
+```bash
+PYTHONPATH=src python examples/ctsd_generation_example.py -c examples/ctsd_35_6views_image_generation.json -o output/ctsd_35_6views_image_generation
+```
+
+For more advanced examples, including layout-conditioned T2V and LiDAR generation, please refer to the [OpenDWM GitHub repository's examples section](https://github.com/SenseTime-FVG/OpenDWM#examples).