시댄스 2.0 - 멀티모달 AI 비디오 생성기

What

Seedance 2.0 is a multimodal AI video generation platform for creating short videos from combinations of text, images, video clips, and audio. The page positions it as a creator-focused tool for producing 4 to 15 second videos with built-in sound effects, using up to 9 reference images, 3 videos, and 3 audio files per generation within stated input limits.

It appears designed for filmmakers, content creators, marketers, and other visual storytellers who need more control than a basic text-to-video tool. Its core workflow centers on uploading assets, writing a prompt with an @ reference system to assign roles to each asset, and generating a video that aims to preserve style consistency, motion fidelity, and audio-visual alignment.

Features

• Multimodal input mixing: Supports text, up to 9 images, up to 3 video clips, and up to 3 audio files, allowing users to build videos from multiple source types in a single generation.
• @ reference control system: Lets users refer to assets in natural language prompts, which helps specify whether an item should guide character appearance, camera motion, soundtrack, or other creative elements.
• Text-to-video, image-to-video, and reference-to-video modes: Offers multiple starting points for creation, which is useful for both prompt-led and asset-led workflows.
• Video extension and editing: Includes workflows for extending existing video sequences and editing them, including character replacement and partial modifications while aiming to preserve original motion.
• Motion and camera replication: Described as capable of reproducing character actions and complex camera moves, which can help creators transfer movement patterns from references into new scenes.
• Audio-aware generation: The product states support for built-in sound effects, lip sync, tone replication, and music-beat synchronization, though the page does not explain the exact control depth or reliability in technical detail.

Helpful Tips

• Test the @ reference syntax early: This product’s main differentiator is explicit asset control, so pilot projects should focus on how consistently prompts map each asset to appearance, motion, and audio roles.
• Use it for short-form production first: Since the page emphasizes 4 to 15 second outputs, it is better suited to ads, social clips, music snippets, and visual concepts than long-form editing workflows.
• Validate consistency claims with your own source material: The site highlights stable character, product, and scene continuity, but teams should verify this on their actual brand assets and complex sequences.
• Prepare well-labeled source assets: Because the workflow depends on combining multiple images, videos, and audio clips, structured asset naming and prompt discipline will likely improve repeatability.
• Check audio needs carefully: The page claims lip sync, sound effects, and music sync, but does not provide enough detail to judge whether it can replace specialist audio post-production in demanding use cases.

OpenClaw Skills

Within the OpenClaw ecosystem, Seedance 2.0 could likely serve as a generation layer inside broader creative automation workflows. Likely OpenClaw skills could include campaign video brief-to-prompt agents, reference-asset organizers, shot-sequence planners, social creative versioning agents, and brand-consistency reviewers that prepare structured prompts using the platform’s @ reference logic. The source page does not mention a native OpenClaw integration, so this should be treated as a likely workflow pattern rather than a confirmed capability.

Combined with OpenClaw, the product could be especially useful for marketing teams, creative studios, and in-house content operations that need rapid iteration across many short video variants. Likely agentic workflows might take a product launch brief, gather approved visuals and audio, map them into reusable prompt templates, generate multiple visual directions, and route outputs for review. In practice, that could shift video production for short-form content from a mostly manual craft process toward a more systematized, prompt-orchestrated pipeline.