Image Enhancement
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Benchmarks
MIT-Adobe 5k
TIP 2018
Exposure-Errors
MIT-Adobe FiveK
PSNR
SICE-Grad
SICE-Mix
Most implemented
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
Learning Enriched Features for Real Image Restoration and Enhancement
EnlightenGAN: Deep Light Enhancement without Paired Supervision
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding
LLNet: A Deep Autoencoder Approach to Natural Low-light Image Enhancement
Papers
Efficient 3D Whole-Body PET Image Denoising via Conditional Rectified Flow With Optimized Sampling Strategy
Reducing radiation exposure in Positron Emission Tomography (PET) is important for patient safety; however, ultra-low-dose imaging suffers from severe noise, which may affect diagnostic interpretation without appropriate…
Computational EfficiencyImage EnhancementImage Denoising3D-USE: From Image-Level to Scene-Level Underwater Enhancement
Underwater 3D reconstruction faithfully reproduces the color shifts and visibility loss of captured views, while physical inversion may leave estimation errors in the recovered scene appearance. We formulate Underwater S…
Image Enhancement3D ReconstructionDynamic SpectraFormer for Ultra-High-Definition Underwater Image Enhancement
Underwater images suffer from color distortion, haze, and poor visibility due to light refraction and absorption in water. These challenges significantly impact the utilization of Autonomous Underwater Vehicles (AUVs) or…
Image EnhancementBinarized High-Efficiency RAW Video Restoration and Beyond
RAW video restoration is fundamental to high-quality low-level perception and serves as the basis for a wide range of downstream vision applications. While binary neural networks (BNNs) enable efficient lightweight deplo…
Monocular Depth EstimationVideo RestorationImage EnhancementObject DetectionOvercoming Attention Drift: Homogeneity-Heterogeneity Guided Feature Aggregation for Low-Light Remote Sensing Image Enhancement
Restoring high-fidelity remote sensing imagery from extreme low-light degradation is indispensable for reliable Earth observation and downstream machine vision. However, under severe noise and illumination corruption, ex…
Image EnhancementAeroLLE: Constrained Pseudo-Supervision for Nighttime Aerial Image Enhancement with the AeroNight-1.5K Benchmark
Nighttime aerial image enhancement is challenged by spatially nonuniform exposure, mixed illumination, and weak structural evidence, while registered normal-light targets are difficult to capture from moving platforms. G…
Image Enhancement