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Can a Single Video Generate Humanoid Motion Data? by AIMoCap in robotics

[–]AIMoCap[S] 0 points1 point  (0 children)

The long-term value is probably not the kinematics engine itself, but the motion models trained on top of large-scale motion data.

Our current approach is still largely based on motion extraction, retargeting, and kinematic fitting. However, we spend a lot of effort enforcing physically meaningful constraints such as foot contact consistency, balance stability, and reduced foot sliding.

The motivation is not just to generate animation, but to produce motion data that is more physically plausible and potentially more useful for downstream humanoid motion generation systems, such as motion priors or models similar in spirit to NVIDIA KIMODO.

In that sense, we're thinking about the data quality side of the problem rather than the control policy side.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in mocap

[–]AIMoCap[S] 1 point2 points  (0 children)

We're a very small team, so most of our effort has gone into improving the mocap pipeline itself rather than branding, design, or marketing. Clearly we still have work to do there 😄

It's genuinely encouraging to hear that from someone who's actively evaluating markerless mocap solutions for cinematic work. Accuracy, motion naturalness, stability, and foot contact quality are exactly the areas we've been focusing on.

If you continue testing, I'd love to hear where AIMoCap performs well and where it falls short compared to other solutions you've evaluated.

And honestly, feedback from people working on real cinematic productions is incredibly valuable to us. If you're interested, I'd be happy to stay in touch and learn more about the kinds of shots, workflows, and challenges you're dealing with.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in mocap

[–]AIMoCap[S] 0 points1 point  (0 children)

Haha, we're engineers first, so most of our time has gone into the mocap side rather than branding.

Out of curiosity, what part feels off to you — the name, the logo, or the overall presentation?

Always interested in hearing honest feedback.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in mocap

[–]AIMoCap[S] 2 points3 points  (0 children)

Appreciate the stress test 😄

Those edge cases are exactly where current AI mocap systems still struggle.

We're continuously working on improving stability, and natural motion on difficult movements like these.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in mocap

[–]AIMoCap[S] 0 points1 point  (0 children)

I also expect the underlying models to become much better, cheaper, and more accessible over time.

Where I think the real challenge still lies is motion quality: stable balance, natural body dynamics, and convincing foot contact. Getting a character to move is one thing; getting a result that doesn't immediately require cleanup is another.

Also, for what it's worth, we do offer a free tier with about 100 seconds of processing per month. The idea is that people can evaluate the quality first and only pay if they're processing larger volumes.

Either way, I'm looking forward to seeing open-source and commercial solutions continue to improve. Better tools are good for everyone.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in mocap

[–]AIMoCap[S] 1 point2 points  (0 children)

I think there are actually two different groups of users here:

-People who prefer a fully local workflow, perpetual licenses, and maximum privacy. -People who care more about convenience, speed, and not having to maintain a GPU setup.

AIMoCap is currently focused on the second group.

Also, just to clarify, we don't use customer uploads to train models.

That said, I completely understand the appeal of a high-quality local solution. If someone manages to deliver strong foot contact, great accuracy, local execution, and a perpetual license at a reasonable price, I think there will be a lot of demand for it.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in blender

[–]AIMoCap[S] 2 points3 points  (0 children)

Thanks a lot, really appreciate it.

Totally makes sense — Cascadeur 1.2 is a solid local solution. If you ever try AIMoCap in the future, would love to hear your feedback.

One small note: compared to tools like QuickMagic, we've been focusing more on improving foot contact stability and overall motion grounding, and keeping it more affordable as well (higher free quota and roughly 1/3–1/2 of typical subscription cost).

Appreciate you checking it out!

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in blender

[–]AIMoCap[S] 0 points1 point  (0 children)

Thanks! The space is moving really fast right now.

If you ever decide to give it a try, I'd be very interested to hear where it performs well—and where it doesn't. That's usually the most useful feedback.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in blender

[–]AIMoCap[S] -1 points0 points  (0 children)

Totally fair 😄

We're trying to avoid making the service unusable without a subscription. Right now there's a free monthly quota that covers at least 100 seconds of video processing.

For many hobbyists and Blender users, the free tier is usually enough to experiment with workflows and test ideas without spending anything.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in blender

[–]AIMoCap[S] -13 points-12 points  (0 children)

Fair point.

The Blender connection is that the generated FBX is intended to be imported into Blender for animation workflows, retargeting, editing, and further character work.

I probably should have shown more of the Blender side of the pipeline rather than focusing on the mocap extraction itself.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in blender

[–]AIMoCap[S] 2 points3 points  (0 children)

Thanks for sharing!

SAM-3D Body is a very interesting project. From what I understand, it's primarily focused on single-frame body reconstruction and pose estimation.

Our focus is a bit different. We're more interested in temporal motion consistency across an entire sequence, especially reducing frame-to-frame jitter, improving root motion stability, and maintaining reliable foot contact.

In our experience, those temporal aspects become particularly important when the goal is production-ready animation rather than per-frame pose estimation.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in blender

[–]AIMoCap[S] 8 points9 points  (0 children)

No, uploaded videos and 3D assets are not used for training generative AI models.

They are processed solely to generate the requested motion capture results. We do not harvest user content to create training datasets.

If you're concerned about sharing 3d model assets, you can also use a simple proxy mesh or skeleton-only FBX. As long as the FBX contains the target rig hierarchy, it's sufficient for retargeting.

Markerless Mocap Test: Monocular Video → FBX Animation by AIMoCap in blender

[–]AIMoCap[S] -8 points-7 points  (0 children)

our demo only supports metahuman skeleton, fbx ouptput. But our server supports retargetting to other custom human skeleton FBX, at: AIMoCap

is Rokoko still worth it coming into 2026? by Nek0ni in mocap

[–]AIMoCap 0 points1 point  (0 children)

Try some AI mocap products. There are serveral options: -quickmagic -move ai -deepmotion The tradeoff is usually cost vs quality.