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编程语言

”lightweight-image-super-resolution“ 的搜索结果

RFDN
@njulj

Residual Feature Distillation Network for Lightweight Image Super-Resolution

Python376
1 年前

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LESRCNN
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#计算机科学#Lightweight Image Super-Resolution with Enhanced CNN (Knowledge-Based Systems,2020)

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Omni-SR
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[CVPR2023] Implementation of ''Omni Aggregation Networks for Lightweight Image Super-Resolution".

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AWSRN
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PyTorch code for our paper "Lightweight Image Super-Resolution with Adaptive Weighted Learning Network"

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Lightweight Image Super-Resolution with Information Multi-distillation Network (ACM MM 2019, Winner Award of ICCVW AIM 2019 Constrained SR Track1&Track2)

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SCNet
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[MIR 24] Fully 1x1 Convolutional Network for Lightweight Image Super-Resolution

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RepRFN
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Reparameterized Residual Feature Network For Lightweight Image Super-Resolution

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SMFANet
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[ECCV 2024] SMFANet: A Lightweight Self-Modulation Feature Aggregation Network for Efficient Image Super-Resolution

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The offical implementation of "Lightweight Image Super-Resolution with Superpixel Token Interaction" (ICCV2023)

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NGramSwin
@rami0205

N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution (CVPR2023 Accepted)

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Tohrusky/Final2x
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2^x Image Super-Resolution

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David Garcia
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Image super-resolution through deep learning

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Image Super-Resolution for Anime-Style Art

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Fast, Accurate and Lightweight Super-Resolution models

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Image and video super resolution

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Image super-resolution using Tensorflow.js .

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#计算机科学#Image super resolution models for PyTorch.

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Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution

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SReC
@caoscott

PyTorch Implementation of "Lossless Image Compression through Super-Resolution"

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Edge Guided Single Depth Image Super-resolution

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#计算机科学#🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

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[IJCV2024] Exploiting Diffusion Prior for Real-World Image Super-Resolution

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#计算机科学#Revisiting RCAN: Improved Training for Image Super-Resolution

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(ECCV2020 Workshops) Efficient Image Super-Resolution Using Pixel Attention.

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