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视频特效全部视频工具

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AI 视频工具/视频放大

视频工具

AI 视频放大器

用 AI 把视频提升到清晰的 1080P、2K 与 4K,提高分辨率并恢复老旧或低质量素材的细节。现可先预览工作流程。

预览video

Video Upscaler

Preview a video upscaler workflow for 1080P, 2K, and 4K outputs.

即将推出

该工作流当前用于规划展示;模型或 API 支持可用后会开放运行。

使用方式

如何使用 视频放大

1

Upload the low-resolution video

Upload the video you want to upscale (up to 120 seconds). SD, 720P, and compressed social media footage are all accepted as source material.

2

Select the target output resolution

Choose 1080P, 2K, or 4K from the settings panel. Runway or Topaz Video AI will reconstruct fine pixel detail at the selected output resolution rather than simply stretching the source.

3

Submit the upscale order

Submit the job. You will receive the high-resolution output once the frame-level reconstruction endpoint becomes generally available. Current status: preview.

为什么使用

为什么使用 AI Pin Maker 视频工具

按工作流组织

每个页面都把一个用户任务映射到所需视频输入和模型族。

模型匹配

当前没有线上端点支持该精确视频工作流,因此生成暂未启用。

预览路线图

预览工具会在正式上线前展示后续视频工作流。

路线衔接

相关视频工具帮助从特效继续到编辑、音乐和生产流程。

常见问题

视频工具常见问题

Is the AI video upscaler currently processing uploads?
The video upscaler is in preview mode. You can configure your upscale job and preview the settings now; full processing launches when the frame-level reconstruction endpoint is live.
What output resolutions does the AI upscaler support?
Target outputs of 1080P, 2K, and 4K are planned. The model reconstructs fine pixel detail rather than simply stretching the source, so the output maintains sharp edges and texture at all three resolutions.
How does AI upscaling differ from software-based interpolation?
Software upscalers like Bicubic interpolation average neighboring pixels, which produces soft edges. AI upscalers use video-conditioned models to predict the high-frequency detail that should logically be present in each frame based on scene content and motion.
Can I upscale footage shot on a phone or old camcorder?
Yes. AI reconstruction is especially effective on classic SD, 720P, or compressed social media footage — where content detail was lost to compression or low sensor resolution rather than inherent scene complexity.

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