MimicX-Assets

Reference motions and reproducibility assets for MimicX. Start with a task's robot reference and its matching policy, preview the recorded executions, or inspect the complete experiment archive. Both repositories are available.

Run One Task

These four references match the recommended final MimicX policies. Download only the pair you need; the full telemetry archive is not required to run it.

Motion	Robot reference	Matching policy	Instructions
Dance	Download reference	Final policy	Run Dance
Football	Download reference	Final policy	Run Football
Kung Fu	Download reference	Final policy	Run Kung Fu
Tennis	Download reference	Final policy	Run Tennis

Recommended reference manifests retain each exact policy/reference identity, checksum and configuration link without copying data. The reference is a robot-motion NPZ, not the source human video. Install the MimicX code and tracking environment before execution.

Watch Recorded Policies

Eight existing robot-only videos, organized by task and method. Each link opens the HF file viewer, where the original MP4 can also be downloaded. Videos show individual recorded rollouts; numerical comparisons use the registered repeated evaluation protocol. The Fixed Reference and MimicX columns remain separate.

Motion	Fixed Reference	MimicX
Dance	Watch / download	Watch / download
Football	Watch / download	Watch / download
Kung Fu	Watch / download	Watch / download
Tennis	Watch / download	Watch / download

Choose Your Download

Goal	Entry point	What you need
Run a policy	Recommended assets	One robot reference and its paired policy
Reproduce the core study	Usage guide, registered input map	Both snapshots and the pinned runtime
Inspect execution-gate decisions	Gate index, replay audit	Recorded telemetry and the code's gate implementation
Inspect HLoop execution	Workload, summary	Archived workload, executor and timing records
Audit all sources and hashes	Reference catalog, provenance, checksums	Full archive

Reproduce and Verify

For a single task, follow its Instructions link above. The supplied prepare-eval command checks that policy and reference against their hashes and prepares execution commands without launching them.

For the complete archive, download both repositories into sibling directories:

hf download Shuaijun/MimicX-Policies --local-dir MimicX-Policies
hf download Shuaijun/MimicX-Assets --repo-type dataset --local-dir MimicX-Assets
python MimicX-Assets/prepare.py verify --root MimicX-Assets
python MimicX-Policies/prepare.py verify --root MimicX-Policies

Full-snapshot verification requires all indexed files; it is not the check for an intentionally selective download. See USAGE.md for reconstructing the 22-file core input bundle, preparing evaluations and replaying all 12 core gates.

Complete Archive

Artifact	Scope
Robot reference motions	10 bundled NPZs; 14 licensed references indexed by identity/hash
Core experiment records	48 final trials across four tasks, four methods and three seeds
Additional video records	24 final trials
Provided-motion breadth	24 final trials
Fresh AMASS/ACCAD retargeting	4 final trials
Execution-gate evidence	12 complete core gates, with all accept/protect outcomes retained
HLoop evidence	Fixed workload, five measured repetitions and warmup records
Robot-only videos	8 recordings: four tasks, two methods

The companion Policies repository holds 161 unique checkpoints and indexes 94 candidate endpoints. Trial identities, candidate endpoints and distinct network files are different counts. Scientific summary tables live in the project website.

During the automated loop, the registered motion stays fixed. The recommended Dance and Kung Fu references are the registered repaired motions; their fixed-reference comparisons use the original motions. HLoop's workload uses the registered Fixed Reference policies, eight rollouts, eight diagnoses and one selection, with no PPO updates. Full policy/training details are in the Policies model card.

Paper and Code

MimicX: Policy-in-the-Loop Supervision Refinement for Video-Driven Humanoid Motion Tracking

• Code and installation
• Paper source
• Project website source and numerical downloads

Data Sources and Reuse

Raw human videos, SMPL-family models/parameters, GVHMR and SONIC pretrained weights, and third-party motion datasets are not redistributed here. The 14 licensed breadth references are represented by identity/hash records only: obtain authorized source data separately. Supplementary policy weights and their execution records are included; those reference inputs are not claimed to be bundled. The historical lafan1_Form_1_stageii_g1 identifier belongs to AMASS/ACCAD Form 1 provided retargeting, not LaFAN1.

See THIRD_PARTY.md and reference_index.json in MimicX-Assets. The license covers the MimicX-authored files in this snapshot and does not grant rights to external datasets or dependencies. Robot reference arrays and recorded tracking errors do not contain SMPL model weights or source RGB frames.

Reproducibility and Provenance

FILES.json and SHA256SUMS.txt identify the released bytes. Checkpoints and bundled motions are copied byte-for-byte. CSV telemetry is gzip compressed; licensed breadth exports omit the three reference-root coordinate columns, while retaining every metric value. Other telemetry exports are lossless. Metadata replaces private paths with artifact URIs and removes machine placement/command details; scientific values and decisions are retained. SOURCE_PROVENANCE.json records both original and public-file hashes. Historical hash fields embedded in logs refer to original files, not sanitized exports. Archived YAML Python tags are inert descriptors, not executable constructors.

Code baseline: 961b114462680e042cdadb04989b8ced6ad75cb7. No new policy learning or GPU experiments were run to create this package. Publication does not make a PyTorch pickle safe to load from an untrusted fork; verify checksums and use a trusted snapshot.

Browse the Files

REFERENCE_CATALOG.md provides a human-readable download/identity table.