Research Brief: Authors: Pranav Jeevan; Akella Srinidhi; Pasunuri Prathiba; Amit Sethi Description: Authors: Yoo, Jinsu; Kim, Taehoon; Lee, Sihaeng; Kim, Seung Hwan; Lee, Honglak; Kim, Tae Hyun* Description: Recent ...

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Authors: Kai Zhang, Luc Van Gool, Radu Timofte Description: Learning-based single Authors: Jie Liu, Wenjie Zhang, Yuting Tang, Jie Tang, Gangshan Wu Description: Recently, very deep convolutional neural ... Authors: Pranav Jeevan; Akella Srinidhi; Pasunuri Prathiba; Amit Sethi Description:

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Authors: Pranav Jeevan; Akella Srinidhi; Pasunuri Prathiba; Amit Sethi Description: Authors: Yoo, Jinsu; Kim, Taehoon; Lee, Sihaeng; Kim, Seung Hwan; Lee, Honglak; Kim, Tae Hyun* Description: Recent ...

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  • Authors: Pranav Jeevan; Akella Srinidhi; Pasunuri Prathiba; Amit Sethi Description:
  • Authors: Yoo, Jinsu; Kim, Taehoon; Lee, Sihaeng; Kim, Seung Hwan; Lee, Honglak; Kim, Tae Hyun* Description: Recent ...
  • Authors: Kai Zhang, Luc Van Gool, Radu Timofte Description: Learning-based single
  • Authors: Jie Liu, Wenjie Zhang, Yuting Tang, Jie Tang, Gangshan Wu Description: Recently, very deep convolutional neural ...

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Supporting Media Notes

Residual Feature Aggregation Network for Image Super-Resolution
953 - MPRNet: Multi-Path Residual Network For Lightweight Single Image Super Resolution
Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution
Learning Texture Transformer Network for Image Super Resolution
Deep Unfolding Network for Image Super-Resolution
Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation
WaveMixSR: Resource-Efficient Neural Network for Image Super-Resolution
Unpaired Image Super-Resolution Using Pseudo-Supervision
Residual Networks (ResNet) [Physics Informed Machine Learning]
Dual Aggregation Transformer for Image Super-Resolution
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Residual Feature Aggregation Network for Image Super-Resolution

Residual Feature Aggregation Network for Image Super-Resolution

Authors: Jie Liu, Wenjie Zhang, Yuting Tang, Jie Tang, Gangshan Wu Description: Recently, very deep convolutional neural ...

953 - MPRNet: Multi-Path Residual Network For Lightweight Single Image Super Resolution

953 - MPRNet: Multi-Path Residual Network For Lightweight Single Image Super Resolution

... and my supervisor angel sappa the paper title is mprnet multipath

Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution

Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution

Authors: Yoo, Jinsu; Kim, Taehoon; Lee, Sihaeng; Kim, Seung Hwan; Lee, Honglak; Kim, Tae Hyun* Description: Recent ...

Learning Texture Transformer Network for Image Super Resolution

Learning Texture Transformer Network for Image Super Resolution

Read more details and related context about Learning Texture Transformer Network for Image Super Resolution.

Deep Unfolding Network for Image Super-Resolution

Deep Unfolding Network for Image Super-Resolution

Authors: Kai Zhang, Luc Van Gool, Radu Timofte Description: Learning-based single

Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation

Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation

Read more details and related context about Recombinator Networks: Learning Coarse-To-Fine Feature Aggregation.

WaveMixSR: Resource-Efficient Neural Network for Image Super-Resolution

WaveMixSR: Resource-Efficient Neural Network for Image Super-Resolution

Authors: Pranav Jeevan; Akella Srinidhi; Pasunuri Prathiba; Amit Sethi Description:

Unpaired Image Super-Resolution Using Pseudo-Supervision

Unpaired Image Super-Resolution Using Pseudo-Supervision

Authors: Shunta Maeda Description: In most studies on learning-based

Residual Networks (ResNet) [Physics Informed Machine Learning]

Residual Networks (ResNet) [Physics Informed Machine Learning]

Read more details and related context about Residual Networks (ResNet) [Physics Informed Machine Learning].

Dual Aggregation Transformer for Image Super-Resolution

Dual Aggregation Transformer for Image Super-Resolution

Read more details and related context about Dual Aggregation Transformer for Image Super-Resolution.