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CMU Takes a Big Step Toward Real-Time Realistic Video Generation Based on Language Descriptions
Oct. 26, 2022, 10:05 p.m. | Synced
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In the new paper Towards Real-Time Text2Video via CLIP-Guided, Pixel-Level Optimization, researchers from Carnegie Mellon University leverage CLIP-guided, pixel-level optimization to generate 720p resolution videos from natural language descriptions at a rate of one-to-two frames per second — taking a big step towards a real-time text-to-video system.
The post CMU Takes a Big Step Toward Real-Time Realistic Video Generation Based on Language Descriptions first appeared on Synced.
ai artificial intelligence big deep-neural-networks language machine learning machine learning & data science ml real-time research technology text2video video video generation
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