Quality gate before scale
Custom characters vary in skeleton structure and pose quality, so a retarget test is the practical gate before using the avatar in automated jobs.
CUSTOM AVATAR API
Custom avatar mocap API planning
Plan AIMoCap API usage around published custom avatar targets, web setup, and repeatable motion jobs.
For teams that want API jobs to use custom avatar targets prepared in Studio.
Short answer
A custom avatar mocap API should let a product run repeatable mocap jobs against character targets that have already been prepared, tested, and published.
When to use AIMoCap
Use AIMoCap when your team prepares avatars in Studio first, then wants API jobs to reuse those published targets for automated video mocap workflows.
When not to use AIMoCap
Do not use this API path to skip avatar setup. New FBX characters still need upload, A-pose, binding, retarget testing, and publish steps before they are reliable targets.
Custom avatar API planning is different from a generic mocap API integration because the target character is part of the pipeline.
AIMoCap keeps avatar preparation and API processing as separate stages: prepare and publish the avatar through the character workflow, then run repeatable API jobs against supported targets.
This boundary helps teams avoid brittle automation. The API job can focus on upload, queueing, polling, and download while the avatar quality gate remains in the Studio retarget-test process.
Custom avatar API boundaries
- Custom avatar targets should be prepared and validated before automation depends on them.
- A-pose editing, skeleton binding, retarget testing, and publish are Studio-side quality steps.
- API jobs are best used after a target is reusable, not as a shortcut around binding review.
- API v-credit is separate from web Studio credits.
- Default FBX output, custom avatar output, and Unitree G1 robot output are distinct target concepts.
- A failed avatar retarget test should be fixed before the character becomes part of an API workflow.
- The public API job lifecycle remains asynchronous: create, upload, complete, poll, and download.
Why custom avatar API needs a setup boundary
Use these facts to decide whether this workflow matches your output, integration, and cleanup needs.
Published target reuse
The API workflow becomes valuable after the avatar is reusable; repeated jobs can then target the same prepared character without redoing setup each time.
Separated accounting
Automated jobs consume API v-credit, while avatar preparation remains a separate Studio workflow and should not be mixed with API usage reporting.
Custom avatar API planning workflow
01
Prepare the avatar before API automation
Upload the FBX character, adjust A-pose if needed, bind the skeleton, run a retarget test, and publish only after the result is approved.
02
Use published targets in repeatable jobs
Once a character target is published, API automation can focus on source video upload, complete-upload, queued processing, polling, and result retrieval.
03
Keep target setup and API usage separate
Avatar setup is a quality gate. API v-credit tracks automated mocap usage separately from web Studio credits and from the one-time character preparation workflow.
Common questions
Can AIMoCap API use custom avatars?
A custom avatar should first be prepared, tested, and published through the character workflow. After that, API planning can treat it as a reusable target for repeatable mocap jobs.
Can I upload a new FBX avatar directly inside every API job?
No. New avatars need a setup and quality workflow: upload, A-pose, binding, retarget test, and publish before they are reliable targets.
Why separate Studio avatar setup from API jobs?
Avatar quality depends on skeleton mapping and retarget results. Keeping setup separate prevents an automated API pipeline from repeatedly failing on an unvalidated character.
Does custom avatar API usage consume web credits?
API mocap jobs use API v-credit. Web Studio credits and API v-credit are tracked separately.
Is a custom avatar target the same as Unitree G1?
No. Custom avatars are animation-character targets. Unitree G1 is a robot-oriented target with different downstream artifacts and validation needs.
Related AIMoCap guides
Continue through this topic cluster to compare output formats, API options, and workflow boundaries.
Sources reviewed
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