#image-processing4 articles

4 articles

AIBullisharXiv – CS AI · 6h ago1

🧠

FAST-DIPS: Adjoint-Free Analytic Steps and Hard-Constrained Likelihood Correction for Diffusion-Prior Inverse Problems

Researchers propose FAST-DIPS, a new training-free diffusion prior method for solving inverse problems that achieves up to 19.5x speedup while maintaining competitive image quality metrics. The method replaces computationally expensive inner optimization loops with closed-form projections and analytic step sizes, significantly reducing the number of required denoiser evaluations.

AINeutralarXiv – CS AI · 6h ago1

🧠

Reparameterized Tensor Ring Functional Decomposition for Multi-Dimensional Data Recovery

Researchers propose a reparameterized Tensor Ring functional decomposition method that uses Implicit Neural Representations to improve multi-dimensional data recovery tasks. The approach addresses limitations in high-frequency modeling through structured reparameterization and demonstrates superior performance in image processing and point cloud recovery applications.

AINeutralarXiv – CS AI · 6h ago0

🧠

You Only Need One Stage: Novel-View Synthesis From A Single Blind Face Image

Researchers developed NVB-Face, a one-stage AI method that generates consistent novel-view face images directly from single low-quality images. The approach bypasses traditional two-stage restoration processes by using feature manipulation and diffusion models to create 3D-aware representations, significantly improving consistency and fidelity.

AINeutralarXiv – CS AI · 6h ago0

🧠

MixerCSeg: An Efficient Mixer Architecture for Crack Segmentation via Decoupled Mamba Attention

Researchers have developed MixerCSeg, a new AI architecture for crack segmentation that combines CNN, Transformer, and Mamba-based approaches to achieve state-of-the-art performance with high efficiency. The model uses only 2.05 GFLOPs and 2.54M parameters while outperforming existing methods on crack detection benchmarks.