Add dataset card and SHA-256 manifest

MANIFEST.sha256

@@ -0,0 +1,10 @@
+06defb8528a6fdb453f585e1533c3660ea784f27cfe350a2263b0b695fe04c00  2objs/01.zip
+9a56ac84dbbb91eb25a5afa3675f832bd7091f2e12392fa6f3b800f0beb274e3  2objs/02.zip
+788af245b9e35bda54498c13132ce146a1e35b57fc840a1e44a02ae843d72b87  2objs/04.zip
+b0802824a35a4eccf423c7841409dd9458e719178917362acdce1273a46a3d1d  2objs/06.zip
+1d4446f5ac9f1c170d24b6b058ffa0cc26378a2fef2f32d2b00e9ea7c3a67103  2objs/23.zip
+afef9386827762f6299e7596980d680c9c4a3b4f1a13ffebf3d53ebc8da64dfd  2objs/24.zip
+c3d9f397efa0e8a08aafe7f0b2e09a0dca2b8704758e541d85f2763d784894c1  2objs/26.zip
+c6df9ad70d6494a492a53860d3fd21adba4599013f155b6d10cfbdd731bdda4f  2objs/45.zip
+8ec47c79b99dc2e62044f5c4b408b36d1ae8bcf2d1e32f4df4c5d42c524257fc  2objs/56.zip
+55a3e0b4ef79eba6f783b50009cfbe1bb7854a20c02bde1b5e5509320f7ce497  2objs/67.zip

README.md

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+---
+license: mit
+pretty_name: FrontierPhysics — Multi-Object Visual Inverse Dynamics
+language:
+  - en
+tags:
+  - frontierphysics
+  - physics
+  - system-identification
+  - mosiv
+size_categories:
+  - n<1K
+---
+
+# FrontierPhysics: Multi-Object Visual Inverse Dynamics
+
+Pinned copies of the upstream files used by **`multi-object-visual-inverse-dynamics`** in
+[FrontierPhysics](https://github.com/benchflow-ai/FrontierPhysics), hosted by
+[BenchFlow](https://huggingface.co/benchflow). The task's image build and its verifier
+download these files from this repository instead of the upstream dataset.
+
+This repository holds the ten two-object scenes the task uses: `2objs/{01,02,04,06,23,24,26,45,56,67}.zip`.
+Each archive is byte-identical to the same path in
+[Hanibel/MOSIV](https://huggingface.co/datasets/Hanibel/MOSIV/tree/bc1e42d3587420765965f6a27b92b4d9fe8bb987)
+at revision `bc1e42d3587420765965f6a27b92b4d9fe8bb987`. `MANIFEST.sha256` lists their SHA-256
+digests in `sha256sum -c` format, and the task's `verifier/reference_manifest.json` pins each
+archive's size and digest.
+
+The archives include the hidden evaluation frames and point clouds. FrontierPhysics uses them only
+in its verifier, and its image build exposes only the observed interval. The task's agent sandbox
+blocks this repository.
+
+## Download
+
+Pin a full commit revision. The FrontierPhysics tasks pin
+`98974d4d2e76868b674605dfa6c9856806134181`.
+
+```python
+from huggingface_hub import hf_hub_download
+
+path = hf_hub_download(
+    repo_id="benchflow/frontierphysics-multi-object-visual-inverse-dynamics",
+    repo_type="dataset",
+    revision="98974d4d2e76868b674605dfa6c9856806134181",
+    filename="2objs/01.zip",
+)
+```
+
+## Attribution and licence
+
+MOSIV is released under the MIT licence by its authors. Please cite:
+
+```
+@misc{liu2026mosivmultiobjectidentificationvideos,
+      title={MOSIV: Multi-Object System Identification from Videos},
+      author={Chunjiang Liu and Xiaoyuan Wang and Qingran Lin and Albert Xiao and Haoyu Chen and Shizheng Wen and Hao Zhang and Lu Qi and Ming-Hsuan Yang and Laszlo A. Jeni and Min Xu and Yizhou Zhao},
+      year={2026},
+      eprint={2603.06022},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2603.06022},
+}
+```
+
+Browse the [FrontierPhysics task datasets collection](https://huggingface.co/collections/benchflow/frontierphysics-task-datasets-6a9e71712c664f5221b85ed1).