This media is not supported in your browser
VIEW IN TELEGRAM
✨FMA-Net++: Motion- and Exposure-Aware Real-World Joint Video Super-Resolution and Deblurring
📝 Summary:
FMA-Net++ addresses joint video super-resolution and deblurring by modeling motion and dynamic exposure. It employs an exposure-aware sequence architecture, decoupling degradation learning from restoration for top accuracy and efficiency.
🔹 Publication Date: Published on Dec 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04390
• PDF: https://arxiv.org/pdf/2512.04390
• Project Page: https://kaist-viclab.github.io/fmanetpp_site/
• Github: https://kaist-viclab.github.io/fmanetpp_site/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#VideoSuperResolution #VideoDeblurring #ComputerVision #DeepLearning #ImageProcessing
📝 Summary:
FMA-Net++ addresses joint video super-resolution and deblurring by modeling motion and dynamic exposure. It employs an exposure-aware sequence architecture, decoupling degradation learning from restoration for top accuracy and efficiency.
🔹 Publication Date: Published on Dec 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04390
• PDF: https://arxiv.org/pdf/2512.04390
• Project Page: https://kaist-viclab.github.io/fmanetpp_site/
• Github: https://kaist-viclab.github.io/fmanetpp_site/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#VideoSuperResolution #VideoDeblurring #ComputerVision #DeepLearning #ImageProcessing
❤3👍1