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Found 7 papers, 5 papers with code
Semi-Supervised State-Space Model with Dynamic Stacking Filter for Real-World Video Deraining
Significant progress has been made in video restoration under rainy conditions over the past decade, largely propelled by advancements in deep learning.
EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture Models
We estimate the range-wise ensemble weights on a reference set and store them in a lookup table (LUT) for efficient ensemble inference on the test set.
A Hybrid Transformer-Mamba Network for Single Image Deraining
Existing deraining Transformers employ self-attention mechanisms with fixed-range windows or along channel dimensions, limiting the exploitation of non-local receptive fields.
Restoring Images in Adverse Weather Conditions via Histogram Transformer
It is powered by a mechanism dubbed histogram self-attention, which sorts and segments spatial features into intensity-based bins.
DI-Retinex: Digital-Imaging Retinex Theory for Low-Light Image Enhancement
Many existing methods for low-light image enhancement (LLIE) based on Retinex theory ignore important factors that affect the validity of this theory in digital imaging, such as noise, quantization error, non-linearity, and dynamic range overflow.
Logit Standardization in Knowledge Distillation
Knowledge distillation involves transferring soft labels from a teacher to a student using a shared temperature-based softmax function.
Rethinking Image Restoration for Object Detection
To address the issue, we propose a targeted adversarial attack in the restoration procedure to boost object detection performance after restoration.
