runwayml/gen4-aleph

A new way to edit, transform and generate video

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Runway Gen-4 Aleph

Runway Aleph is an in-context video model that performs comprehensive video editing and transformation tasks on input videos. The model handles object manipulation, scene generation, environmental changes, and visual transformations through text prompts or reference images.

When attributing to Runway, please use “Powered by Runway” and link to runwayml.com from the user interface.

Core Capabilities

Camera and Shot Generation

  • Novel View Generation: Create new camera angles from existing footage (reverse shots, low angles, medium shots)
  • Shot Continuation: Generate seamless next shots in video sequences
  • Motion Transfer: Apply camera motion from one video to a new starting frame

Object Manipulation

  • Object Addition: Insert new elements into scenes (crowds, products, props, fireworks) with proper lighting and perspective
  • Object Removal: Remove unwanted elements or distracting objects from footage
  • Object Replacement: Replace or retexture existing objects using text prompts or reference images
  • Green Screen Extraction: Isolate subjects with precise edge detection for transparent or colored backgrounds

Environmental and Atmospheric Changes

  • Location/Environment Modification: Change settings, locations, seasons, and time of day
  • Weather Effects: Add atmospheric elements like rain or other weather conditions
  • Lighting Adjustment: Transform lighting conditions (golden hour, dawn, sunset) with natural shadow and reflection updates

Visual Style and Appearance

  • Style Transfer: Apply aesthetic styles to footage using reference materials
  • Character Appearance: Modify actor age and appearance through text prompts
  • Color Modification: Change object colors using color swatches or descriptive prompts
  • Relighting: Adjust scene mood and lighting conditions

Technical Specifications

  • Model Type: In-context video generation and manipulation
  • Input Methods: Text prompts, reference images, color swatches
  • Processing: Multi-task operations on input video files
  • Output: Modified video content with maintained scene coherence

Key Features

  • Preserves lighting, shadows, and perspective when adding elements
  • Maintains temporal consistency across video frames
  • Handles complex transformations while retaining source footage elements
  • Supports both additive and subtractive editing operations
  • Processes multiple editing tasks within single operations

Limitations

  • Results depend on input video quality and complexity
  • Performance varies based on scene content and modification requests
  • Subject to model training constraints and algorithmic boundaries