MS-SSIM
52 papers with code • 1 benchmarks • 0 datasets
A MS-SSIM score helps to analyze how much a De-warping module has been able to de-warp a document image from its initial distorted view.
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Use these libraries to find MS-SSIM models and implementationsLatest papers
S2LIC: Learned Image Compression with the SwinV2 Block, Adaptive Channel-wise and Global-inter Attention Context
In this paper, we propose an Adaptive Channel-wise and Global-inter attention Context (ACGC) entropy model, which can efficiently achieve dual feature aggregation in both inter-slice and intraslice contexts.
SLIC: A Learned Image Codec Using Structure and Color
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.
Using Diffusion Models to Generate Synthetic Labelled Data for Medical Image Segmentation
Improvements over GAN methods were seen on average when the segmenter was entirely trained (DL difference: $-0. 0880 \pm 0. 0170$, IoU difference: $0. 0993 \pm 0. 01493$) or augmented (DL difference: GAN $-0. 1140 \pm 0. 0900 \text{ vs SD }-0. 1053 \pm 0. 0981$, IoU difference: GAN $0. 01533 \pm 0. 03831 \text{ vs SD }0. 0255 \pm 0. 0454$) with synthetic data.
The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric
We show how perceptual embeddings of the visual system can be constructed at inference-time with no training data or deep neural network features.
Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model
The proposed model consists of two processes: a forward process which adds Gaussian noise to real CT scans, and a reverse process in which a shifted-window transformer V-net (Swin-Vnet) denoises the noisy CT scans conditioned on the MRI from the same patient to produce noise-free CT scans.
MMVC: Learned Multi-Mode Video Compression with Block-based Prediction Mode Selection and Density-Adaptive Entropy Coding
In this paper, we propose multi-mode video compression (MMVC), a block wise mode ensemble deep video compression framework that selects the optimal mode for feature domain prediction adapting to different motion patterns.
UVDoc: Neural Grid-based Document Unwarping
In this paper we propose a novel method for grid-based single-image document unwarping.
Reference Guided Image Inpainting using Facial Attributes
Image inpainting is a technique of completing missing pixels such as occluded region restoration, distracting objects removal, and facial completion.
Advancing Learned Video Compression with In-loop Frame Prediction
In this paper, we propose an Advanced Learned Video Compression (ALVC) approach with the in-loop frame prediction module, which is able to effectively predict the target frame from the previously compressed frames, without consuming any bit-rate.
PO-ELIC: Perception-Oriented Efficient Learned Image Coding
In the past years, learned image compression (LIC) has achieved remarkable performance.