CUSTOM AVATAR
Upload, bind, test, and publish custom avatars in AIMoCap so video mocap jobs can reuse them as output targets.
For animation teams looking for custom character retargeting in a video mocap workflow.
AIMoCap lets teams upload, bind, retarget-test, publish, and reuse custom avatars as Studio output targets.
Use it when repeated mocap jobs should target your own character instead of only a default animation target.
Do not skip binding and retarget testing; source asset quality and skeleton structure still determine whether the avatar is reusable.
AIMoCap includes a custom avatar workflow for teams that need motion output on their own character rather than only a default target.
After upload, A-pose editing, binding, retarget testing, and publish, a custom avatar can be reused inside Studio.
This page is about the reusable target lifecycle, not only file upload. The important decision is whether the character has passed enough setup and test steps to become safe for repeated mocap jobs.
The practical value is repeatability. A custom avatar should have a known source asset, binding decision, test clip result, publish state, and limitations before teams use it across many mocap jobs.
Custom avatar retargeting is most useful after the avatar has passed setup checks; the decision is whether the character is ready to become a reusable target.
Character artists and technical animators usually ask what happens after upload: pose assumptions, skeleton mapping, retarget test quality, and whether the target is reusable.
A common objection is that a model can upload successfully but still fail as a production target, so binding and retarget tests need to stay central.
A-pose mismatch, unusual hierarchy, scale, and limb mapping can affect whether a custom avatar is useful, even when the source video is readable.
The strongest workflow benefit is not one-off retargeting, but preparing a character once and reusing it across future mocap jobs.
Use these facts to decide whether this workflow matches your output, integration, and cleanup needs.
A published avatar can be selected again in Studio, which makes the upfront binding and test step useful for repeated jobs.
A retarget test acts as the practical quality gate before an uploaded character becomes a reusable mocap target.
Custom avatars are animation-character targets; Unitree G1 remains a separate robot-motion target.
A draft avatar can contain source assets and mapping work, while a published avatar is the version intended for repeated Studio job selection.
Users searching for custom avatar retargeting usually need upload, A-pose, binding, test, publish, and reuse details, not only a generic video mocap pitch.
A custom-avatar page is more useful when it separates avatar setup failures from source-video failures, because both can produce poor motion on the final character.
A reusable avatar target should be accepted or rejected based on playback on that character, not only on default preview quality.
Recording limitations makes future jobs easier to review because teams know which issues are avatar setup, source-video quality, or expected cleanup.
Start by creating a character profile and uploading the source FBX asset.
Edit the A-pose when needed, map the skeleton, and run a retarget test before publishing.
Once the retarget result is approved, publish the avatar so it can be selected for future mocap jobs.
Treat uploaded or partially bound characters as draft assets until the retarget test proves the target is ready for reuse.
After publishing, record known limitations such as hand reach, shoulder twist, foot contact, scale, or source-video types that require cleanup.
Yes. A custom avatar can be uploaded, bound, tested, published, and then reused as an output target.
The retarget test helps confirm that the skeleton mapping and motion result are usable before the avatar becomes a reusable target.
Yes. Published custom avatars can be selected as output targets in Studio.
No. Upload is only the first step. The avatar still needs A-pose review, skeleton binding, and a retarget test before it should be published for reuse.
A draft avatar is still being prepared or tested. A published avatar has passed the workflow and can be selected again as a Studio output target.
Do not publish it if the retarget test fails on the motions you expect to reuse, or if scale, A-pose, skeleton mapping, hand reach, or foot contact still need setup work.
Check the source FBX, A-pose, skeleton binding, scale, root orientation, left/right mapping, retarget test result, and whether the source video is readable enough for the intended motion.
Continue through this topic cluster to compare output formats, API options, and workflow boundaries.
Prepare clips that reduce retargeting cleanup.
Compare default FBX, custom targets, and robot outputs.
Upload, bind, test, and publish FBX avatars so AIMoCap video mocap jobs can reuse them as targets.
Use AIMoCap Studio to prepare a custom character target, then reuse it in future video mocap jobs.
A practical overview of AIMoCap avatar upload, A-pose, skeleton binding, test, publish, and reuse.
Prepare reusable custom avatar targets for AIMoCap so source video can drive your own character workflow.
These related AIMoCap resources document the workflow boundaries, output formats, and implementation details referenced on this page.
