Hz Unity Face Tracking logo

Hz Unity Face Tracking

Organization
meta-quest
hz-unity-face-tracking

Drive ARKit-blendshape-rigged head/face models in Unity with the wearer's facial expressions on Meta Quest via Meta Movement SDK (face tracking + A2E). Use when a user has an FBX with the 52 ARKit blendshapes (any prefix, _L/_R suffixes) and wants it to animate from face tracking on Quest Pro / Quest 3 / Quest 3S.

Overview

Publishermeta-quest
Repositoryagentic-tools
Skill namehz-unity-face-tracking
Stars
195
Forks
17
Bundled files
2
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by meta-quest on GitHub. Read the source before you install it.

Installation

Install the Hz Unity Face Tracking AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/meta-quest/agentic-tools.git /tmp/agentic-tools
mkdir -p .claude/skills
cp -r /tmp/agentic-tools/skills/hz-unity-face-tracking .claude/skills/hz-unity-face-tracking
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hz Unity Face Tracking in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hz Unity Face Tracking on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hz Unity Face Tracking is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Unity Face Tracking for ARKit-Rigged Models (Meta Movement SDK)

End-to-end recipe to make a head/face model rigged with the standard 52 ARKit blendshapes animate from the wearer's face on Quest. Uses the public OVRCustomFace extension hook — no OVR_INTERNAL_CODE, ships to 3P.

The model's blendshape names must follow the ARKit naming convention (camelCase, _L/_R suffixes, e.g. eyeBlink_L, jawOpen, mouthSmile_R). An optional prefix like blendShape2.eyeBlink_L is automatically stripped.

When to use

  • User has an FBX/GLB/mesh with ARKit-named blendshapes and wants it driven by Quest face tracking.
  • User asks: "animate this head with my face", "drive these blendshapes from face tracking", "use Movement SDK A2E with my model", "wire ARKit shapes to Quest".
  • Target device: Quest Pro, Quest 3, Quest 3S (Quest 2 is no-op — no face cameras).

Prerequisites checklist

  1. Quest face tracking-capable headset (Pro / 3 / 3S).
  2. Packages in Packages/manifest.json:
    • com.meta.xr.sdk.core (Meta XR Core — provides OVRFaceExpressions, OVRCustomFace)
    • com.meta.xr.sdk.movement (Meta Movement SDK — A2E + retargeting helpers)
  3. Assets/Oculus/OculusProjectConfig.asset (verify via Project Settings → Meta XR):
    • faceTrackingSupport: 1 (Supported) or 2 (Required)
    • eyeTrackingSupport: 1 if the rig has gaze
  4. Android manifest (Assets/Plugins/Android/AndroidManifest.xml) permissions:
    • <uses-feature android:name="oculus.software.face_tracking" android:required="false" />
    • <uses-permission android:name="com.oculus.permission.FACE_TRACKING" />
    • <uses-permission android:name="android.permission.RECORD_AUDIO" /> (required for A2E)
    • For eye gaze: oculus.software.eye_tracking + com.oculus.permission.EYE_TRACKING
  5. OVRCameraRig in the scene with OVRManager.FaceTrackingDataSources including Audio (A2E) — if you skip Audio, mouth motion is visual-only.

After any change to OculusProjectConfig, call meta_update_android_manifest to regenerate the manifest.

Approach (high level)

  1. Drop the ARKitOVRCustomFace script (in references/ARKitOVRCustomFace.cs) into the project.
  2. Add an OVRFaceExpressions component to the OVRCameraRig (or anywhere in the scene).
  3. On the GameObject that has the model's SkinnedMeshRenderer, add ARKitOVRCustomFace. Adding the component triggers Reset(), which auto-populates the blendshape→FaceExpression mapping by scanning the mesh's blendshape names.
  4. Wire the component's FaceExpressions field to the OVRFaceExpressions instance.
  5. For eye gaze: drop ARKitEyeGazeBlendshapeDriver in (see Eye tracking below).
  6. Press Play with Meta XR Link, or build APK and side-load. On first launch, accept the Face Tracking / Eye Tracking / Microphone permission prompts.

That's the whole flow. Details below.

Eye tracking (DO THIS — face expressions alone don't work)

Don't rely on OVRFaceExpressions.EyesLook* for eye gaze. Those fields are derived from face-camera visuals, not the dedicated eye tracker. On Quest Pro they're often zero or noisy even when face tracking is otherwise working. The right API is OVREyeGaze, which taps the eye tracker directly.

For ARKit rigs with eyeLook* blendshapes (no eye bones), this skill ships ARKitEyeGazeBlendshapeDriver:

  • Reads gaze rotation from two OVREyeGaze components (one per eye, TrackingMode = HeadSpace).
  • Computes rotation relative to a head reference (e.g. CenterEyeAnchor).
  • Decomposes pitch → eyeLookUp/Down_{L,R}, yaw → eyeLookIn/Out_{L,R} (with the ARKit "_In = toward nose" convention).
  • Writes weights in LateUpdate, so it overrides whatever ARKitOVRCustomFace wrote in Update.

For rigs with eye bones (no eyeLook* blendshapes), skip the blendshape decomposition and just parent OVREyeGaze to each eye bone with ApplyRotation = true — the component will rotate the bone directly.

Eye gaze setup (blendshape rigs)

  1. Create two empty GameObjects under CenterEyeAnchor (or your head transform): LeftEyeGaze, RightEyeGaze.
  2. Add OVREyeGaze to each. Set Eye = Left / Right, TrackingMode = HeadSpace, ApplyPosition = false, ApplyRotation = true, ConfidenceThreshold = 0.5.
  3. Add ARKitEyeGazeBlendshapeDriver to the head's SkinnedMeshRenderer GameObject (alongside ARKitOVRCustomFace). Wire leftEye, rightEye, and referenceFrame (= CenterEyeAnchor).
  4. Tweak maxAngleDeg (default 30°) and smoothing (default 0.4) to taste.

Step-by-step

1. Install the script

Copy references/ARKitOVRCustomFace.cs into Assets/Scripts/ARKitOVRCustomFace.cs. It defines the public, 3P-shippable ARKit ↔ OVR FaceExpression table and a MapBlendshapes() method that scans SkinnedMeshRenderer.sharedMesh.GetBlendShapeName(i), strips any prefix before the last ., lowercases, and matches against the table. Unmatched mesh blendshapes are set to OVRFaceExpressions.FaceExpression.Max (sentinel — skipped at runtime).

2. Enable Movement SDK + permissions

Project settings:

Project Settings → Meta XR → Face Tracking Support = Supported
Project Settings → Meta XR → Eye Tracking Support = Supported (if needed)

Then regenerate manifest:

  • Unity MCP: meta_update_android_manifest
  • Or Editor menu: Meta → Tools → Update AndroidManifest.xml

3. Scene setup

Scene Hierarchy
├── OVRCameraRig                         (from meta_add_camerarig)
│   └── (add) OVRFaceExpressions         component
└── YourHeadModel
    └── ...SkinnedMeshRenderer GO...
        ├── SkinnedMeshRenderer          (existing)
        └── (add) ARKitOVRCustomFace     component
             └── FaceExpressions = the OVRFaceExpressions ref
             └── retargetingType = Custom (set automatically by base when overriding)
             └── Mappings[] = auto-filled on Reset()
             └── BlendShapeStrengthMultiplier = 100 (default; OVR weights are 0–1, mesh wants 0–100)

If the head has multiple SkinnedMeshRenderers (e.g. separate teeth/tongue meshes), add ARKitOVRCustomFace to each one.

4. OVRManager — enable Audio as a data source (A2E)

On OVRCameraRig's OVRManager component:

  • Face Tracking Data Sources → check Visual AND Audio (Audio = A2E; produces mouth shapes from microphone when the visual face cameras can't see something — talking, occlusion, etc.).

5. Trigger the mapping if the component already existed

MapBlendshapes() runs automatically when the component is added (Reset()) and from OnValidate() when Mappings is empty. If you need to remap manually (e.g. after re-importing the FBX), use the component's inspector context menu → Map Blendshapes, or from a script:

csharp
go.GetComponent<ARKitOVRCustomFace>().MapBlendshapes();

From Unity MCP Unity_RunCommand, the cleanest invocation (the OVR/MSDK types aren't referenced in the MCP dynamic assembly, so use SendMessage to avoid reflection):

csharp
GameObject.Find("YourHeadModel")
    .GetComponentInChildren<SkinnedMeshRenderer>().gameObject
    .SendMessage("MapBlendshapes", SendMessageOptions.RequireReceiver);

6. Verify

  • In Editor, with Meta XR Link / Quest Link, enter Play mode and make faces. The model should mirror them.
  • On device, build APK, side-load, grant Face Tracking + Microphone permissions on first launch.
  • Check the mapping at edit time: inspect the ARKitOVRCustomFace component. Mappings.Length should equal SkinnedMeshRenderer.sharedMesh.blendShapeCount. The Console log from MapBlendshapes() reports mapped X/N blendshapes — X should be 50 (or 52 if the FBX has all of them).

Troubleshooting

SymptomCause / fix
mapped 0/N in ConsoleMesh blendshape names don't follow ARKit convention. Verify with mesh.GetBlendShapeName(i). Names must match e.g. eyeBlink_L, jawOpen — case-insensitive, prefix before last . is stripped.
Face is frozenOVRFaceExpressions not assigned, or scene has no OVRCameraRig/OVRManager with face tracking enabled. Check OVRFaceExpressions.FaceTrackingEnabled and ValidExpressions at runtime.
Mouth doesn't move when speakingA2E disabled. Enable Audio under OVRManager → Face Tracking Data Sources, and ensure RECORD_AUDIO permission is granted on device.
Eyes don't blinkMesh's eyelid shapes aren't named eyeBlink_L/_R. Either rename, or add a custom row to ARKitTable.
Eyes don't move (look around)You're relying on OVRFaceExpressions.EyesLook* instead of OVREyeGaze — switch to ARKitEyeGazeBlendshapeDriver.
Eye gaze in wrong directionNote the deliberate ARKit ↔ OVR swap: ARKit's eyeLookIn_L (eye looking nose-ward, i.e. right) maps to OVR EyesLookRightL. The table already does this — don't "fix" it.
Weights look half-strength or clampedBlendShapeStrengthMultiplier defaults to 100 because Unity blendshapes are 0–100 while OVR is 0–1. Don't lower this unless intentional.
cannot change access modifiers when overriding compile errorBase method is protected internal in another assembly. The override must use protected (not protected internal) — already correct in the supplied script.
_mappings out of sync with shared mesh assertion at StartMesh changed since mapping was generated. Re-run MapBlendshapes() via the component context menu.

ARKit ↔ OVR FaceExpression mapping (reference)

The 52 ARKit shapes don't 1:1 a FACS-based OVR enum. Notable choices baked into ARKitTable:

  • Centrally-named ARKit shapes that have L+R OVR pairs (browInnerUp, cheekPuff, mouthFunnel, mouthPucker, mouthRollLower, mouthRollUpper) pick only the L-side OVR expression. If your model has obviously asymmetric mouth/brow when the user uses these expressions and you want true symmetric drive, subclass and additively sum L+R in a custom MapBlendshapes (use SlothARKitFaceDriver-style per-blendshape sum). For most heads the L-only choice is fine because the face is roughly symmetric and the asymmetry is below visual threshold.
  • eyeLookIn/Out are deliberately swapped per side relative to OVR's left/right semantics (see Troubleshooting).
  • mouthCloseLipsToward (closest FACS analogue).
  • tongueOutTongueOut (requires HorizonOS ≥ 65 + tongue tracking; otherwise stays at 0).

Files in this skill

  • SKILL.md — this file
  • references/ARKitOVRCustomFace.cs — drop-in OVRCustomFace subclass
  • references/ARKitEyeGazeBlendshapeDriver.cs — OVREyeGaze → eyeLook* blendshape driver (LateUpdate)

Why this approach (vs. alternatives)

  • Custom MonoBehaviour driver that reads OVRFaceExpressions[expr] and writes blendshape weights directly: works, but doesn't integrate with MSDK's correctives, eye constraints, or future retargeting upgrades. Use only if you can't extend OVRCustomFace.
  • OVRCustomFace + RetargetingType.ARKitBlendshapes: clean, but guarded behind #if OVR_INTERNAL_CODE in the public Oculus Integration package — not 3P-shippable.
  • OVRCustomFace + RetargetingType.Custom + GetCustomBlendShapeNameAndExpressionPairs override (this skill): fully public API, shippable, and gets all base-class behavior (data validity gating, weight scaling, mesh assertion).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Hz Unity Face Tracking AI skill do?

Drive ARKit-blendshape-rigged head/face models in Unity with the wearer's facial expressions on Meta Quest via Meta Movement SDK (face tracking + A2E). Use when a user has an FBX with the 52 ARKit blendshapes (any prefix, _L/_R suffixes) and wants it to animate from face tracking on Quest Pro / Quest 3 / Quest 3S.

Why use Hz Unity Face Tracking on TypingMind?

Because you install it once and use it with any model. Hz Unity Face Tracking is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hz Unity Face Tracking in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/meta-quest/agentic-tools/tree/main/skills/hz-unity-face-tracking. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Hz Unity Face Tracking?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hz Unity Face Tracking?

As many as you like. As long as a model supports skills, you can use Hz Unity Face Tracking with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hz Unity Face Tracking AI skill free?

Yes. It is published on GitHub by meta-quest under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇