Possible Reality’s Intract technology was a real prototype for putting a player’s face on an existing game character, but it was not a full-body scan or a feature anyone could use in any game. A 2020 demonstration used one 256-by-256-pixel face image to texture an animated avatar in Unity. The original report described developer alpha testing; whether Intract remains available or supported today is unverified.
What was Possible Reality’s Intract?
Possible Reality was a Los Angeles startup that, according to GamesBeat’s report, originally published October 15, 2020 and marked updated June 18, 2025, began in 2018. The report identified founder Ryan Isbell and lead developer Levon Ravel. The company’s Intract technology was intended to let game developers add a player’s likeness to existing characters, with an API and developer trials rather than a finished consumer game.
Its pitch addressed a familiar tension in character creators: manual sliders can take time, while a recognizable face can make a player feel more present in a game. Possible Reality presented its approach as a visual customization layer—closer to a character skin than a new game or a complete digital double. The report described an opportunity, not confirmed adoption by a named released game or evidence of commercial success.
How did the demonstration work?
- A user supplied a face photo from a phone, webcam, or another source.
- Intract adapted the visible facial information for a compatible character.
- The face was applied to an animated avatar and rendered in Unity.
- Other appearance details, such as hair and eyes, could be handled through the game’s character-creation tools.
The GamesBeat demonstration used a single 256-by-256-pixel image. The report described the result as imperfect and focused on adapting the face to a character, rather than rebuilding the character around a complete scan of the user.
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Was Intract a face scan or a full digital twin?
No. A single portrait does not directly reveal the back and sides of a head or all of its three-dimensional geometry. Intract’s reported approach used a photo to adapt a face to a pre-existing character. It did not claim to capture the user’s whole body, reproduce every part of the skull and facial anatomy, or automatically create hair, clothing, voice, and animation.
The distinction matters because “put my face in a game” can describe several different outputs:
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| Approach | Typical input | What it produces |
|---|---|---|
| Face texture or adaptation | One face photo | A likeness applied to an existing head or character |
| Single-image character generation | One portrait | Predicted facial shape and texture fitted to a game character |
| 3D face scanning | Guided capture or multiple views | A three-dimensional head, sometimes rigged |
| Real-time face tracking | Live camera feed | Expression and movement controls for an avatar |
| Full digital-twin creation | More extensive capture and processing | A broader asset that may include face, body, materials, rig, and animation |
The AAAI paper on MeInGame describes the broader challenge of turning a portrait into facial shape and texture for a 3D game character. It contrasts that with character creators that rely on manual parameter adjustment and with multi-view mobile scanning, which requires more capture effort and several angles.
What could go wrong technically?
A face photo is incomplete evidence about a three-dimensional person. Shadows, uneven lighting, glasses, hair, facial hair, makeup, and other obstructions can change what the system sees. The face also has to fit the target model’s proportions, topology, UV layout, materials, and lighting; a texture that looks plausible from the front may look pasted on from another angle.
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- Mismatch with the character: A realistic face on a stylized head or body can look uncanny.
- Limited views: One image cannot reliably supply details hidden from the camera, so identity may shift as the character turns.
- Static likeness: Applying a face does not itself create a facial rig, blend shapes, or camera tracking for expressions.
- Integration work: Developers still need compatible character assets, materials, animation, performance budgets, and platform support.
- Incomplete personalization: Face adaptation alone does not recreate body shape, hair simulation, clothing, or voice.
The MeInGame paper likewise frames automatic facial shape and texture creation as a technical problem, rather than a matter of simply pasting a picture onto a model.
Is Possible Reality or Intract available now?
The historical report established that Intract was in alpha testing and that Possible Reality offered developer trials. It does not establish that the product is publicly available, commercially supported, or integrated into a released game in 2026. The linked Possible Reality website does not provide enough visible product detail to confirm current availability. That is an unknown, not proof that the company or technology has shut down.
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For ordinary players, there is no verified basis to expect a consumer Intract download. For developers, the evidence does not confirm a current API, supported engine versions, documentation, pricing, or support terms. Those should be verified directly before planning a production pipeline.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What current tools are closest to the idea?
There is no single direct replacement among the examples below: they address scanning, social avatars, or animation rather than all the same tasks Intract proposed.
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| Tool or category | What it does | Best fit | Important limit |
|---|---|---|---|
| Copresence | Markets phone-based face scanning, photorealistic 3D avatars, and platform and API access. | Developers or creators evaluating a 3D avatar asset for games, XR, or telepresence. | It is more focused on 3D avatar capture than face-texturing an existing character. Public developer/API pricing is not stated on the cited site. |
| REALITY | Provides customizable anime-style 3D avatars, broadcasting, and social features. | Consumers, streamers, and VTubers seeking a stylized hosted avatar experience. | It is not a general-purpose photorealistic face asset or SDK for arbitrary games. The U.S. App Store listing marks it free with in-app purchases. |
| EmbodyMe Beta | A historical VR app that created a realistic avatar from one face photo. | Readers exploring an earlier experiment in photo-based avatars. | Steam’s listing identifies it as free-to-play and warns its last developer update was more than nine years ago; it is not a dependable current production recommendation. |
| NVIDIA Audio2Face | Provides audio-driven facial animation and character-authoring workflows. | Technical artists animating an existing 3D character from voice or audio. | It animates a model; it does not create the player’s likeness from a selfie. See NVIDIA’s Audio2Face page. |
| Built-in game face creator or scan | Uses a particular game’s own tools to create or import a player likeness. | Players who want a likeness in that specific title. | Availability and output depend on the individual game; it does not imply a portable asset for other games. |
Copresence says its capture takes about a minute and avatar generation takes minutes, and presents both platform and API paths. Its site also advertises a free scan, but does not state public developer/API pricing. Check its current terms and technical documentation before relying on those capabilities.
How should developers evaluate a face-to-avatar service?
A demo image is not enough to establish that an asset will work in a shipped game. Before choosing a vendor or building an integration, check:
- Output: Is the result a texture, mesh, rigged head, full avatar, or an asset hosted only inside the vendor’s platform?
- Pipeline fit: Which engines, file formats, skeletons, materials, and target platforms are supported?
- Capture requirements: Is one photo sufficient, or does capture require a guided scan or multiple views? What resolution and lighting are expected?
- Identity and animation: Does the asset preserve likeness across angles, and does it include facial rigging or tracking?
- Processing and privacy: Is processing local or cloud-based? How long are source images and derived data retained, and can users delete them?
- Rights and safety: Who may use the generated likeness, and what controls address non-consensual uploads, impersonation, and abuse?
- Commercial terms: Confirm pricing, usage limits, redistribution rights, and support commitments directly with the provider.
What privacy and consent issues matter?
A face photo can identify a person, and some uses of facial data may be treated as biometric processing depending on jurisdiction. A game or avatar service should explain how uploads and derived data are processed, retained, deleted, and used for model training. Cloud processing can add retention and breach risks, so check the service’s own privacy terms rather than assuming a face image is harmless.
Consent matters just as much as storage. A tool that accepts arbitrary photos can be misused to impersonate someone or create a misleading likeness. Developers should set rules for whose images users may submit and build moderation and reporting processes appropriate to their audience, especially where minors or user-generated content are involved.
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