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Open access Jul 2026

ERD: Extended RAW-Diffusion Framework for De-rendering sRGB Images

This paper builds upon the RAW-Diffusion model and incorporates a ControlNet-guided architecture that provides structured conditioning to improve generalization without requiring metadata at inference time, and demonstrates that the proposed ControlNet-enhanced model enhances reconstruction accuracy on unseen sensors.

Jiaqi Shang, Yifan Qu, Jianbo Qi · 0 citations
Jul 2026

IDAM-RAW: a sensor-aware RAW imaging framework for low-light perception via illumination decoupling and adaptive feature modulation

This paper proposes IDAM-RAW, a unified RAW-domain framework that bridges physical imaging processes and detection-oriented representation learning through task-driven end-to-end optimization, and DetISP maps RAW measurements to detection-friendly features without relying on fixed hardware ISP processing.

Min-Jie Dai, Xing-Yu Lai · 0 citations
Aug 2026

Low-light image enhancement technology based on vision transformer

This work validates the design effectiveness of decoupling global and local representations within a frozen backbone, and establishes a new baseline for parameter-efficient enhancement.

Yan-Peng Cao, Yue Wang, Ming-Hui Liang et al. · 0 citations
Preprint Aug 2026

LiteKD-Net: Lightweight Knowledge-Distilled Network for Mobile Image Denoising

LiteKD-Net, a lightweight knowledge-distilled network for mobile image denoising that reaches great reduction in runtime and increase in the inference rate with good restoration quality and computational efficiency, is proposed.

Zhi-Yi Zhou · 0 citations
Open access Aug 2026

Binarized High-Efficiency RAW Video Restoration and Beyond.

This paper proposes BinRVR, a binarized RAW video restoration framework that reduces computation and parameters by approximately 96% while incurring only about 4% performance degradation, and develops a Distribution-Aware Binarized Convolution (DAB-Conv) that leverages the statistics of full-precision activations to mi...

Tianyu Zhu, Ying Fu, He-Song Li et al. · 0 citations
Open access Aug 2026

Deep Edge-Aware Post-Processing for JPEG Enhancement: CNN-Based Artifact Reduction and Image Quality Restoration

A CNN-based edge-aware artifact reduction framework (CNN-AR) is proposed that integrates an enhanced deep super-resolution (EDSR) backbone with a holistically nested edge detection (HED) guided loss, enabling superior artifact suppression while preserving fine structural details.

Nupur, Nishant Kumar, Sajal Suhane et al. · 0 citations

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