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Found 8 papers, 7 papers with code
DemosaicFormer: Coarse-to-Fine Demosaicing Network for HybridEVS Camera
Coarse demosaicing network is designed to produce a preliminary high-quality estimate of the RGB image from the HybridEVS raw data while the pixel correction network enhances the performance of image restoration and mitigates the impact of defective pixels.
MIPI 2024 Challenge on Demosaic for HybridEVS Camera: Methods and Results
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
HomoFormer: Homogenized Transformer for Image Shadow Removal
The spatial non-uniformity and diverse patterns of shadow degradation conflict with the weight sharing manner of dominant models which may lead to an unsatisfactory compromise.
Ranked #3 on
Shadow Removal
on ISTD+
Revisiting Single Image Reflection Removal In the Wild
This research focuses on the issue of single-image reflection removal (SIRR) in real-world conditions, examining it from two angles: the collection pipeline of real reflection pairs and the perception of real reflection locations.
Learning Weather-General and Weather-Specific Features for Image Restoration Under Multiple Adverse Weather Conditions
Inspired by this observation, we design an efficient unified framework with a two-stage training strategy to explore the weather-general and weather-specific features.
Model Generalization: A Sharpness Aware Optimization Perspective
Sharpness-Aware Minimization (SAM) and adaptive sharpness-aware minimization (ASAM) aim to improve the model generalization.
Efficient Model-Driven Network for Shadow Removal
To address these issues, we first propose a new shadow illumination model for the shadow removal task.
Bijective Mapping Network for Shadow Removal
Shadow removal, which aims to restore the background in the shadow regions, is challenging due to the highly ill-posed nature.
Ranked #8 on
Shadow Removal
on ISTD+
