SSIM
306 papers with code • 1 benchmarks • 4 datasets
Libraries
Use these libraries to find SSIM models and implementations
O-HAZE
I-HAZE
VIDIT
DRealSR
Latest papers
A Lightweight Inception Boosted U-Net Neural Network for Routability Prediction
harleyhk/ibunet
•
•
As the modern CPU, GPU, and NPU chip design complexity and transistor counts keep increasing, and with the relentless shrinking of semiconductor technology nodes to nearly 1 nanometer, the placement and routing have gradually become the two most pivotal processes in modern very-large-scale-integrated (VLSI) circuit back-end design.
SLIC: A Learned Image Codec Using Structure and Color
InterDigitalInc/CompressAI
•
•
We propose the structure and color based learned image codec (SLIC) in which the task of compression is split into that of luminance and chrominance.
Machine Perceptual Quality: Evaluating the Impact of Severe Lossy Compression on Audio and Image Models
Our results indicate three key findings: (1) using generative compression, it is feasible to leverage highly compressed data while incurring a negligible impact on machine perceptual quality; (2) machine perceptual quality correlates strongly with deep similarity metrics, indicating a crucial role of these metrics in the development of machine-oriented codecs; and (3) using lossy compressed datasets, (e. g. ImageNet) for pre-training can lead to counter-intuitive scenarios where lossy compression increases machine perceptual quality rather than degrading it.
OrthoSeisnet: Seismic Inversion through Orthogonal Multi-scale Frequency Domain U-Net for Geophysical Exploration
However, the detection of sparse thin layers within seismic datasets presents a significant challenge due to the ill-posed nature and poor non-linearity of the problem.
TSGAN: An Optical-to-SAR Dual Conditional GAN for Optical based SAR Temporal Shifting
We propose a novel approach, termed SAR Temporal Shifting, which inputs an optical data from the desired timestamp along with a SAR data from a different temporal point but with a consistent viewing geometry as the expected SAR data, both complemented with a change map of optical data during the intervening period.
Progressive Frequency-Aware Network for Laparoscopic Image Desmoking
jlzcode/pfan
•
•
Laparoscopic surgery offers minimally invasive procedures with better patient outcomes, but smoke presence challenges visibility and safety.
STEREOFOG -- Computational DeFogging via Image-to-Image Translation on a real-world Dataset
Image-to-Image translation (I2I) is a subtype of Machine Learning (ML) that has tremendous potential in applications where two domains of images and the need for translation between the two exist, such as the removal of fog.
Deeper into Self-Supervised Monocular Indoor Depth Estimation
One is the large areas of low-texture regions and the other is the complex ego-motion on indoor training datasets.
Investigating the use of publicly available natural videos to learn Dynamic MR image reconstruction
olivier-jaubert/image_reconstruction_inter4k
•
•
Purpose: To develop and assess a deep learning (DL) pipeline to learn dynamic MR image reconstruction from publicly available natural videos (Inter4K).
FusionFrames: Efficient Architectural Aspects for Text-to-Video Generation Pipeline
The first stage concerns keyframes synthesis to figure the storyline of a video, while the second one is devoted to interpolation frames generation to make movements of the scene and objects smooth.
