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Act-two API

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模型概覽

關於 Act-two

Runway Act-Two API on Runbridge.ai

Quick answer: Runway Act-Two is a Runway video-generation and editing model for character performance transfer. It is intended to animate a character from performance reference material. Teams can evaluate it for character dialogue scenes and performance-driven animation tests. Runbridge includes this model in its catalog; check the current callable ID, endpoint, and supported controls in the API documentation before deployment.

What is Runway Act-Two?

Runway Act-Two belongs to the Runway model family and addresses character performance transfer. Its defining role is to animate a character from performance reference material. This makes it relevant when an application needs a workflow suited to character dialogue scenes, rather than a general model chosen only by brand or benchmark position.

Start with a real task and an explicit definition of an acceptable result. For this model, a second task around performance-driven animation tests helps show whether the same strength holds across different inputs. Provider capabilities and the controls exposed by a gateway route are separate questions; verify both before promising a feature to application users.

Runway Act-Two model profile

ItemDetail
ProviderRunway
Runbridge catalog Model IDact-two
Model typeVideo-generation and editing model
Typical inputSource video or performance media
Typical outputTransformed video clips
Primary taskCharacter performance transfer

Runway Act-Two core capabilities

Character performance transfer

The model is intended to animate a character from performance reference material. That distinction matters when a general-purpose route would require additional processing or would not preserve the inputs this task depends on. Design the application around the task's real output requirements, then test the advertised capability on varied inputs. Keep both successful and failed examples; they reveal where the model adds value and where a fallback or reviewer is needed.

Input-to-output workflow

A typical task starts with source video or performance media and seeks transformed video clips. Use a source clip with clear subjects and motion, then state exactly what should change and what should be preserved. The current Runbridge route may expose only a subset of provider controls, so confirm supported inputs, settings, and outputs before building the user interface around them.

Model-specific details

The Runbridge catalog describes these attributes. Check numeric limits and endpoint-dependent behavior against the active model route before relying on them:

  • Core task: Performance capture and character animation

Runway Act-Two input and output design

  • Prepare the input: Provide source footage and a precise change-and-preserve brief. Include a small set of difficult examples, not only an ideal demonstration.
  • Confirm route controls: Check source-clip limits, edit controls, and task polling. Record the actual callable ID and request fields before wiring a production client.
  • Review the result: Inspect joins, identity, timing, and frame-level artifacts. Save accepted and rejected examples so future model changes can be evaluated on the same basis.

Runway Act-Two practical use cases

Character dialogue scenes

Supply the source performance, character asset, and timing reference required by the workflow. Inspect Runway Act-Two's result for expression, mouth timing, identity preservation, and frame-to-frame stability. Compare the result with the team's current manual or model-assisted baseline. This scenario is a good fit when the model reduces rework without losing details that matter to the final audience.

Performance-driven animation tests

Supply the source performance, character asset, and timing reference required by the workflow. Inspect Runway Act-Two's result for expression, mouth timing, identity preservation, and frame-to-frame stability. Use a second task set with different subjects, lengths, or source quality. This helps show whether the capability still works when inputs are less ideal.

Post-production concept exploration

Prepare a small batch of production-like tasks and record every accepted result, retry, and manual edit. Review temporal continuity, identity preservation, transformation accuracy, render time, and frame-level defects. A controlled pilot turns capability claims into measurable selection criteria for a deployment decision.

Runway Act-Two vs Runway Aleph 2

Choose Runway Act-Two when the central requirement is character performance transfer. Runway Aleph 2 is a related option whose catalog positioning centers on video transformation. This is a task-fit comparison, not a universal quality ranking. Run equivalent tasks through both workflows and compare accepted-output rate, correction effort, turnaround time, and relevant media constraints. A simpler route can be preferable if it meets the same acceptance bar.

Side-by-side selection matrix

Decision pointRunway Act-TwoRunway Aleph 2
Catalog positioningCharacter performance transferVideo transformation
Workflow distinctionAnimate a character from performance reference materialModify existing footage through a video-editing workflow
Typical input to testSource video or performance mediaSource video or performance media
Output to reviewTransformed video clipsTransformed video clips
First comparison questionDoes it meet the acceptance bar for character dialogue scenes?Does it meet the same bar with less correction work?

Use the matrix to choose workflows for evaluation, then confirm any numeric limits on the active model route. Build one shared task set and keep reviewers and scoring rules constant. When input patterns differ, use equivalent briefs and compare the complete workflows rather than isolated model calls. Record rejected outputs as carefully as approved ones; the reasons for rejection often decide which route belongs in production.

Selection rules for this workload

Choose this model for a pilot when the main job is character dialogue scenes and the secondary requirement is performance-driven animation tests. Test the related option when its focus on video transformation also fits the task. For either route, require a minimum accepted-output rate and a maximum correction budget before calling it a fit. Use a separate holdout set to check whether the apparent advantage survives new examples rather than only the prompts used while tuning.

How to access Runway Act-Two on Runbridge.ai

  1. Find Runway Act-Two in the Runbridge model catalog and check whether the route is enabled for your account.
  2. The Runbridge catalog labels act-two as its Model ID. Confirm in the API documentation that this exact value is accepted by the intended route before sending requests.
  3. Upload or reference the source clip as documented, submit the edit task, and retrieve the finished video.
  4. Test one minimal request, inspect its response or task status, then add retries, monitoring, and fallback behavior.

Runway Act-Two evaluation and limitations

Review input constraints, identity and motion continuity, render time, and retrieval. Input clip length, file size, transformation controls, and delivery mode can differ across video endpoints. Confirm model availability, rate limits, content restrictions, and result delivery as well. A catalog entry does not establish production availability or a service-level guarantee.

Use three evaluation rounds. First, run clean examples to confirm the basic input and output path. Second, add ambiguous, low-quality, and constraint-heavy inputs that resemble real user traffic. Third, rerun the same set after prompt or route changes, comparing accepted-output rate, reviewer time, and failure categories.

幾件值得了解的事

常見問題

What is Runway Act-Two best used for?+

Runway Act-Two is positioned for character performance transfer. It is most relevant to evaluate for character dialogue scenes and performance-driven animation tests, using your own acceptance criteria.

What core task is listed for Runway Act-Two?+

The current catalog description lists core task as Performance capture and character animation. Check the active route and provider documentation before relying on this value.

How do I access Runway Act-Two on Runbridge.ai?+

Find Runway Act-Two in the Runbridge model catalog, then copy the current callable ID and endpoint from its API documentation. Verify authentication and response handling before deploying.

Can Runway Act-Two transfer a recorded performance?+

The model description positions it to animate a character from performance reference material. Check the active Runbridge route for the required input format and controls.

What should I test before deploying Runway Act-Two?+

Review temporal continuity, identity preservation, transformation accuracy, render time, and frame-level defects. Input clip length, file size, transformation controls, and delivery mode can differ across video endpoints.

How does Runway Act-Two compare with Runway Aleph 2?+

Runway Act-Two focuses on character performance transfer, while Runway Aleph 2 is positioned for video transformation. Compare equivalent tasks and the complete workflows; neither is universally better.

What input and output does the Runway Act-Two API use?+

The typical workflow takes source video or performance media and returns transformed video clips. Confirm exact formats, limits, and request fields in the current API documentation.

Is Runway Act-Two suitable for character dialogue scenes?+

It is a relevant candidate. Supply the source performance, character asset, and timing reference required by the workflow. Inspect Runway Act-Two's result for expression, mouth timing, identity preservation, and frame-to-frame stability.

API 文件

Sample code and API

Use the Act-two API to integrate powerful AI capabilities into your applications.

POST/runwayml/v1/character_performance
curl -sS --fail-with-body "https://api.runbridge.ai/runwayml/v1/character_performance" \
  -H "Authorization: Bearer $RUNBRIDGEAI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "act_two", "character": {"type": "image", "uri": "https://example.com/character.jpg"}, "reference": {"type": "video", "uri": "https://example.com/performance.mp4"}}'
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