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Caption Remover
Remove hardcoded captions from short MP4 videos by selecting one fixed caption area and processing it online.
AI videovideo editingcaption removerhardcoded subtitlesMP4
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Editor's Take
Curated by Startup List teamCaption Remover is a browser-based tool for removing burned-in captions from short H.264 MP4 videos. Upload a video up to 50 MB and 60 seconds, select one fixed rectangular caption region, run STTN-based video inpainting, and download the processed MP4. Original audio is preserved when supported. No account is required during the public beta. Results vary with motion and mask coverage; the current version does not automatically detect captions or track moving text.
Key Highlights
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Actively discovered by our community
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AI Video
Category classification
Listed Sept 2026
On Startup List since launch
What's Great
- ✓No account required; preserves original audio when supported; simple fixed-region workflow.
What Could Improve
- ✗50 MB and 60-second limits; fixed region only; no automatic caption detection or moving-text tracking.
Use Cases
Software Development
Accelerate your development workflow with AI-powered code generation, debugging, and refactoring.
Video Production
Generate and edit professional video content with AI-powered tools and effects.
Team Productivity
Integrate Caption Remover into your workflow to save hours every week.
Best For
- •Founders in AI Video who need a practical tool for execution
- •Teams that want faster output with less operational overhead
- •Operators looking for actionable insights and repeatable workflows
Caption Remover FAQs
What is Caption Remover best used for?
Remove hardcoded captions from short MP4 videos by selecting one fixed caption area and processing it online.
Is Caption Remover suitable for early-stage startups?
Caption Remover can be suitable for early-stage teams, especially when speed and focused execution matter more than large team complexity.
How does Caption Remover compare to alternatives?
Compare Caption Remover against alternatives on Startup List by reviewing category peers, pricing model, ratings, and use-case alignment.
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