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CLIP-RL: Inpainting de vídeo en bucle cerrado con aprendizaje por refuerzo guiado por detección
Meng Wang1, Jing Ren1, Bing Wang1
1Faculty of Information Engineering and Automation, Kunming University of Science and Technology, 727 South Jingming Road, Kunming 650500, China.
Sensors (Basel, Switzerland)
|January 28, 2026
Resumen
Este estudio presenta CLIP-RL, un marco novedoso de aprendizaje por refuerzo para el inpainting de vídeo. CLIP-RL optimiza las estrategias de inpainting de forma adaptativa, mejorando significativamente la coherencia temporal y la calidad visual en tareas de restauración de vídeo.
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