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eess.IV2026

Deep Scene-Driven Ordering of Hadamard Basis for Single-Pixel Spectral Imaging

Brayan Monroy, Hans Garcia, Henry Arguello +1

The paper introduces a deep learning framework that orders the Hadamard basis adaptively to scene content for single‑pixel spectral imaging, improving visual and near‑infrared imag…

eess.IV2026

Learning to Recorrupt: Noise Distribution Agnostic Self-Supervised Image Denoising

Brayan Monroy, Jorge Bacca, Julián Tachella

Self-supervised image denoising methods have traditionally relied on either architectural constraints or specialized loss functions that require prior knowledge of the noise distri…

eess.IV2026

Scale Equivariance Regularization and Feature Lifting in High Dynamic Range Modulo Imaging

Brayan Monroy, Jorge Bacca

Modulo imaging enables high dynamic range (HDR) acquisition by cyclically wrapping saturated intensities, but accurate reconstruction remains challenging due to ambiguities between…

eess.IV2026

Deep Lightweight Unrolled Network for High Dynamic Range Modulo Imaging

Brayan Monroy, Jorge Bacca

Modulo-Imaging (MI) offers a promising alternative for expanding the dynamic range of images by resetting the signal intensity when it reaches the saturation level. Subsequently, h…

eess.IV2025

DeepInverse: A Python package for solving imaging inverse problems with deep learning

Julián Tachella, Matthieu Terris, Samuel Hurault +24

DeepInverse is an open-source PyTorch-based library for solving imaging inverse problems. The library covers all crucial steps in image reconstruction from the efficient implementa…

eess.IV2025

Autoregressive High-Order Finite Difference Modulo Imaging: High-Dynamic Range for Computer Vision Applications

Brayan Monroy, Kebin Contreras, Jorge Bacca

High dynamic range (HDR) imaging is vital for capturing the full range of light tones in scenes, essential for computer vision tasks such as autonomous driving. Standard commercial…