✨ ARFlow Example Page (#5320)

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### What

### Checklist
* [x] I have read and agree to [Contributor
Guide](https://github.com/rerun-io/rerun/blob/main/CONTRIBUTING.md) and
the [Code of
Conduct](https://github.com/rerun-io/rerun/blob/main/CODE_OF_CONDUCT.md)
* [x] I've included a screenshot or gif (if applicable)
* [x] I have tested the web demo (if applicable):
* Using newly built examples:
[app.rerun.io](https://app.rerun.io/pr/5320/index.html)
* Using examples from latest `main` build:
[app.rerun.io](https://app.rerun.io/pr/5320/index.html?manifest_url=https://app.rerun.io/version/main/examples_manifest.json)
* Using full set of examples from `nightly` build:
[app.rerun.io](https://app.rerun.io/pr/5320/index.html?manifest_url=https://app.rerun.io/version/nightly/examples_manifest.json)
* [x] The PR title and labels are set such as to maximize their
usefulness for the next release's CHANGELOG
* [x] If applicable, add a new check to the [release
checklist](https://github.com/rerun-io/rerun/blob/main/tests/python/release_checklist)!

- [PR Build Summary](https://build.rerun.io/pr/5320)
- [Docs
preview](https://rerun.io/preview/89411852bafcc6707d5541bec8e1e59f3c23ac7a/docs)
<!--DOCS-PREVIEW-->
- [Examples
preview](https://rerun.io/preview/89411852bafcc6707d5541bec8e1e59f3c23ac7a/examples)
<!--EXAMPLES-PREVIEW-->
- [Recent benchmark results](https://build.rerun.io/graphs/crates.html)
- [Wasm size tracking](https://build.rerun.io/graphs/sizes.html)

Follow up on #4121. Sorry for the extremely long delay. But we had
several important developments in Unity and XR streaming. We released an
individual project
[ARFlow](https://github.com/cake-lab/ARFlow?tab=readme-ov-file) that
contains more comprehensive streaming and visualization supports. We
also released [Paper](https://doi.org/10.1145/3638550.3643617), [Project
Page](https://cake.wpi.edu/ARFlow/), and
[Video](https://youtu.be/mml8YrCgfTk).

[![Demo
video](https://img.youtube.com/vi/mml8YrCgfTk/maxresdefault.jpg)](https://youtu.be/mml8YrCgfTk)

For this PR, I followed your previous recommendation of submitting a
paper visualization-style example page. It looks like you have
screenshot images served at `static.rerun.io`, and you might need a few
short videos for the website (like this
[page](https://www.rerun.io/examples/paper-visualizations/shape_pointe)).
Let me know if I can help with that. Thanks!

---------

Co-authored-by: Andreas Reich <r_andreas2@web.de>

docs/cspell.json

@@ -16,6 +16,7 @@
     "andreas",
     "Angjoo",
     "Ankush",
+    "arflow",
     "arkit",
     "arkitscene",
     "arkitscenes",
@@ -45,6 +46,7 @@
     "binstall",
     "binutils",
     "Birkl",
+    "booktitle",
     "braindump",
     "bringup",
     "callstack",
@@ -139,12 +141,14 @@
     "Hawksbill",
     "Heewoo",
     "hickups",
+    "HOTMOBILE",
     "howto",
     "hstack",
     "Huggingface",
     "icosphere",
     "imgmsg",
     "impls",
+    "inproceedings",
     "interner",
     "intrinsics",
     "ipynb",
@@ -222,6 +226,7 @@
     "Nikhila",
     "nohash",
     "noqa",
+    "numpages",
     "numpy",
     "nuScenes",
     "nyud",
@@ -340,6 +345,7 @@
     "Tewari",
     "Texcoord",
     "thiserror",
+    "Tian",
     "timepanel",
     "timepoint",
     "timepoints",
@@ -401,11 +407,14 @@
     "xyzw",
     "Yifan",
     "Yilun",
+    "Yiqin",
     "yourdfpy",
     "yourname",
     "Yusuf",
     "YXHW",
     "YXYX",
+    "zhao",
+    "Zhao",
     "zipfile",
     "Zisserman",
     "zrezke",

examples/manifest.toml

@@ -75,6 +75,7 @@ examples = [
   "slahmr",
   "tapir",
   "widebaseline",
+  "arflow",
 ]
 
 [categories.setup]

examples/python/arflow/README.md

@@ -0,0 +1,48 @@
+<!--[metadata]
+title = "ARFlow: A Framework for Simplifying AR Experimentation Workflow"
+source = "https://github.com/cake-lab/ARFlow"
+tags = ["3D", "Augmented Reality", "Spatial Computing"]
+thumbnail = "https://static.rerun.io/arflow/cc3b0c748e8fc49a78b33631a7005ede3fce44be/480w.png"
+thumbnail_dimensions = [480, 261]
+-->
+
+
+[Paper](https://doi.org/10.1145/3638550.3643617) | [BibTeX](#bibtex) | [Project Page](https://cake.wpi.edu/ARFlow/) | [Video](https://youtu.be/mml8YrCgfTk)
+
+
+ARFlow is designed to lower the barrier for AR researchers to evaluate ideas in hours instead of weeks or months, following:
+- **Efficient AR experiment data collection** from various data sources, including camera, depth sensors, and IMU sensors with an efficient thin mobile client.
+- Flexible AR runtime data **management** with **real-time visualization** (powered by Rerun).
+- **Easy integration** with existing AR research projects without breaking the experimentation logic.
+
+Watch our demo video:
+
+[![Demo video](https://img.youtube.com/vi/mml8YrCgfTk/maxresdefault.jpg)](https://youtu.be/mml8YrCgfTk)
+
+
+## Get Started
+
+Please check our [project repo](https://github.com/cake-lab/ARFlow/blob/main/README.md), and refer to the individual [server](https://github.com/cake-lab/ARFlow/blob/main/python/README.md) and [client](https://github.com/cake-lab/ARFlow/blob/main/unity/README.md) installation guides.
+
+## Citation
+
+Please add the following citation in your publication if you used our code for your research project.
+
+```bibtex
+@inproceedings{zhao2024arflow,
+author = {Zhao, Yiqin and Guo, Tian},
+title = {Demo: ARFlow: A Framework for Simplifying AR Experimentation Workflow},
+year = {2024},
+isbn = {9798400704970},
+publisher = {Association for Computing Machinery},
+address = {New York, NY, USA},
+url = {https://doi.org/10.1145/3638550.3643617},
+doi = {10.1145/3638550.3643617},
+abstract = {The recent advancement in computer vision and XR hardware has ignited the community's interest in AR systems research. Similar to traditional systems research, the evaluation of AR systems involves capturing real-world data with AR hardware and iteratively evaluating the targeted system designs [1]. However, it is challenging to conduct scalable and reproducible AR experimentation [2] due to two key reasons. First, there is a lack of integrated framework support in real-world data capturing, which makes it a time-consuming process. Second, AR data often exhibits characteristics, including temporal and spatial variations, and is in a multi-modal format, which makes it difficult to conduct controlled evaluations.},
+booktitle = {Proceedings of the 25th International Workshop on Mobile Computing Systems and Applications},
+pages = {154},
+numpages = {1},
+location = {<conf-loc>, <city>San Diego</city>, <state>CA</state>, <country>USA</country>, </conf-loc>},
+series = {HOTMOBILE '24}
+}
+```