Image Reconstruction
531 papers with code • 5 benchmarks • 7 datasets
Benchmarks
These leaderboards are used to track progress in Image Reconstruction
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Libraries
Use these libraries to find Image Reconstruction models and implementations
General-100
CED
SEN12MS-CR
SEN12MS-CR-TS
Latest papers with no code
HybridFlow: Infusing Continuity into Masked Codebook for Extreme Low-Bitrate Image Compression
This paper investigates the challenging problem of learned image compression (LIC) with extreme low bitrates.
Multi-feature Reconstruction Network using Crossed-mask Restoration for Unsupervised Anomaly Detection
Unsupervised anomaly detection using only normal samples is of great significance for quality inspection in industrial manufacturing.
MindTuner: Cross-Subject Visual Decoding with Visual Fingerprint and Semantic Correction
Decoding natural visual scenes from brain activity has flourished, with extensive research in single-subject tasks and, however, less in cross-subject tasks.
DensePANet: An improved generative adversarial network for photoacoustic tomography image reconstruction from sparse data
In this study, we proposed an end-to-end method called DensePANet to solve the problem of PAT image reconstruction from sparse data.
Event Cameras Meet SPADs for High-Speed, Low-Bandwidth Imaging
Traditional cameras face a trade-off between low-light performance and high-speed imaging: longer exposure times to capture sufficient light results in motion blur, whereas shorter exposures result in Poisson-corrupted noisy images.
Diffusion assisted image reconstruction in optoacoustic tomography
In this paper we consider the problem of acoustic inversion in the context of the optoacoustic tomography image reconstruction problem.
Multi-Branch Generative Models for Multichannel Imaging with an Application to PET/CT Joint Reconstruction
This paper presents a proof-of-concept approach for learned synergistic reconstruction of medical images using multi-branch generative models.
Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach
This study aims to explore the untapped potential of attention mechanisms incorporated with a deep learning model within the context of the CMR reconstruction problem.
Alljoined -- A dataset for EEG-to-Image decoding
We present Alljoined, a dataset built specifically for EEG-to-Image decoding.
CodeEnhance: A Codebook-Driven Approach for Low-Light Image Enhancement
Low-light image enhancement (LLIE) aims to improve low-illumination images.
