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3D Object Super-Resolution

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3D object super-resolution is the task of up-sampling 3D objects.

<span style="color:grey; opacity: 0.6">( Image credit: Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/weizhou-geek/SFSN

공식 코드

Image Super-Resolution Quality Assessment: Structural Fidelity Versus Statistical Naturalness

https://github.com/weizhou-geek/srif

공식 코드

Quality Assessment of Image Super-Resolution: Balancing Deterministic and Statistical Fidelity

https://github.com/wentxul/linr

공식 코드

Revisiting Implicit Neural Representations in Low-Level Vision

https://github.com/wenyu1009/rtsrn

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Pixel Adapter: A Graph-Based Post-Processing Approach for Scene Text Image Super-Resolution

https://github.com/wgcban/DIP-HyperKite

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Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction

https://github.com/wgcban/HyperTransformer

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HyperTransformer: A Textural and Spectral Feature Fusion Transformer for Pansharpening

https://github.com/williamyang1991/styleganex

공식 코드

StyleGANEX: StyleGAN-Based Manipulation Beyond Cropped Aligned Faces

https://github.com/wl082013/ESIM_dataset

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EventSR: From Asynchronous Events to Image Reconstruction, Restoration, and Super-Resolution via End-to-End Adversarial Learning

https://github.com/wlydlut/uhd-image-restoration-survey

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Deep Learning-Driven Ultra-High-Definition Image Restoration: A Survey

https://github.com/worldstrat/worldstrat

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Open High-Resolution Satellite Imagery: The WorldStrat Dataset -- With Application to Super-Resolution

https://github.com/wqlevi/disgan

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DISGAN: Wavelet-informed Discriminator Guides GAN to MRI Super-resolution with Noise Cleaning

https://github.com/wujunde/medsegdiff

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MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model

https://github.com/wustl-cig/mbdl_pruning

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Efficient Model-Based Deep Learning via Network Pruning and Fine-Tuning

https://github.com/wut-ai/hypersound

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Hypernetworks build Implicit Neural Representations of Sounds

https://github.com/wuyushuwys/compiler-aware-nas-sr

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Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution

https://github.com/wwangcece/sgdm

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Semantic Guided Large Scale Factor Remote Sensing Image Super-resolution with Generative Diffusion Prior

https://github.com/wxxxxxxh/A2F-SR

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Lightweight Single-Image Super-Resolution Network with Attentive Auxiliary Feature Learning

https://github.com/wyf0912/sinsr

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SinSR: Diffusion-Based Image Super-Resolution in a Single Step

https://github.com/wyhuai/ddnm

공식 코드

Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model

https://github.com/wyhuai/rnd

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GAN Prior based Null-Space Learning for Consistent Super-Resolution

https://github.com/wzhshi/MSSRNet

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Single Image Super-Resolution with Dilated Convolution based Multi-Scale Information Learning Inception Module

https://github.com/xahidbuffon/Deep-SESR

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Simultaneous Enhancement and Super-Resolution of Underwater Imagery for Improved Visual Perception

https://github.com/xahidbuffon/srdrm

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Underwater Image Super-Resolution using Deep Residual Multipliers

https://github.com/xaimi-lab/mcmrsr

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Transformer-empowered Multi-scale Contextual Matching and Aggregation for Multi-contrast MRI Super-resolution

https://github.com/xian1234/deeplight

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DeepLight: Reconstructing High-Resolution Observations of Nighttime Light With Multi-Modal Remote Sensing Data

https://github.com/xiaogang00/dp3df

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Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super Resolution

https://github.com/xiaom233/bsrn

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Blueprint Separable Residual Network for Efficient Image Super-Resolution

https://github.com/xieenze/TextSR

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TextSR: Content-Aware Text Super-Resolution Guided by Recognition

https://github.com/xiely-123/shisrcnet

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SHISRCNet: Super-resolution And Classification Network For Low-resolution Breast Cancer Histopathology Image

https://github.com/xiezw5/Component-Divide-and-Conquer-for-Real-World-Image-Super-Resolution

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Component Divide-and-Conquer for Real-World Image Super-Resolution

https://github.com/xinDW/RFGANM

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High-throughput, high-resolution registration-free generated adversarial network microscopy

https://github.com/xindongzhang/elan

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Efficient Long-Range Attention Network for Image Super-resolution

https://github.com/xinntao/EDVR

공식 코드

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

https://github.com/xinntao/ESRGAN

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ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/xinntao/Real-ESRGAN

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Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

https://github.com/xinntao/SFTGAN

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Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.