✨Upsample Anything: A Simple and Hard to Beat Baseline for Feature Upsampling

📝 Summary:
Upsample Anything is a novel test-time optimization framework that enhances low-resolution features to high-resolution outputs without training. It learns an anisotropic Gaussian kernel per image, acting as a universal edge-aware operator. This method achieves state-of-the-art results in tasks li...

🔹 Publication Date: Published on Nov 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.16301
• PDF: https://arxiv.org/pdf/2511.16301

==================================

For more data science resources:
✓ https://t.iss.one/DataScienceT

#Upsampling #ComputerVision #ImageProcessing #DeepLearning #AI

✨POLARIS: Projection-Orthogonal Least Squares for Robust and Adaptive Inversion in Diffusion Models

📝 Summary:
POLARIS minimizes approximate noise errors in diffusion models during image inversion. It robustly treats the guidance scale as a step-wise variable, significantly improving image editing and restoration accuracy by reducing errors at each step.

🔹 Publication Date: Published on Nov 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.00369
• PDF: https://arxiv.org/pdf/2512.00369
• Project Page: https://polaris-code-official.github.io/
• Github: https://github.com/Chatonz/POLARIS

==================================

For more data science resources:
✓ https://t.iss.one/DataScienceT

#DiffusionModels #ImageProcessing #AI #MachineLearning #ComputerVision

✨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

✨RL-AWB: Deep Reinforcement Learning for Auto White Balance Correction in Low-Light Night-time Scenes

📝 Summary:
RL-AWB is a novel framework combining statistical methods with deep reinforcement learning for improved nighttime auto white balance. It is the first RL approach for color constancy, mimicking expert tuning. This method shows superior generalization across various lighting conditions, and a new m...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05249
• PDF: https://arxiv.org/pdf/2601.05249
• Project Page: https://ntuneillee.github.io/research/rl-awb/

==================================

For more data science resources:
✓ https://t.iss.one/DataScienceT

#ReinforcementLearning #ComputerVision #ImageProcessing #AutoWhiteBalance #LowLightImaging

✨RL-AWB: Deep Reinforcement Learning for Auto White Balance Correction in Low-Light Night-time Scenes

📝 Summary:
RL-AWB is a novel framework for nighttime auto white balance. It combines statistical methods with deep reinforcement learning, mimicking expert tuning to improve color constancy in low-light scenes. The method shows superior generalization across various lighting conditions and includes a new mu...

🔹 Publication Date: Published on Jan 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.05249
• PDF: https://arxiv.org/pdf/2601.05249
• Project Page: https://ntuneillee.github.io/research/rl-awb/
• Github: https://github.com/BrianChen1120/RL-AWB

==================================

For more data science resources:
✓ https://t.iss.one/DataScienceT

#ReinforcementLearning #DeepLearning #ComputerVision #ImageProcessing #AWB