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API for Generating Talking Videos

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API for Generating Talking Videos

Hey HN — I’m Gaurav, one of the founders of Captions. We work on applied AI research for talking videos. Our foundation model, Lipdub, captures how humans speak, and matches full face movement to what’s being said. The model is zero-shot and can generate videos in under a minute, without person-specific training. Building on Lipdub, we’re releasing a few APIs that can generate and translate talking videos in bulk. Here are some ways they could be used: * Translating videos with matching lip movement * Creating personalized videos that include someone’s name or company, like what’s shown in this demo ( https://captions-cdn.xyz/api-demo/api-demo-gaurav.mp4 ) We’d love to get feedback from the HN community and hear what you think! You can read all of our documentation here: https://help.captions.ai/api-reference/api And try it out here: https://www.captions.ai/api

Visit productView on Hacker NewsAug 22, 2024
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Product HuntOn track for Day 1 leaderboard · Strong signals: model, apis · Missing: mac, agents, macos
85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: personal, video, way · Missing: mobile apps, ios, entrepreneurs
55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · Missing: arr, mrr, revenue
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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