Papers with Code 아카이브

Image Editing

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

5

평가표

2

보존된 평가 기록

12

코드

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

https://github.com/mducducd/Shadow-Removal

Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data

https://github.com/mducducd/ghost-free-shadow-removal

Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data

https://github.com/mv-lab/InstructIR

InstructPix2Pix: Learning to Follow Image Editing Instructions

https://github.com/nachifur/DMTN

Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN

https://github.com/neverbiasu/ComfyUI-BAGEL

Emerging Properties in Unified Multimodal Pretraining

https://github.com/nikulshr/resnet_fpga

Unrolling Ternary Neural Networks

https://github.com/ppak1991cy/RIS-GAN

RIS-GAN: Explore Residual and Illumination with Generative Adversarial Networks for Shadow Removal

https://github.com/rbgirshick/DeepPyramid

Deformable Part Models are Convolutional Neural Networks

https://github.com/sjames40/smug_journal

SMUG: Towards robust MRI reconstruction by smoothed unrolling

https://github.com/sreenivas88/LP-IOANet

LP-IOANet: Efficient High Resolution Document Shadow Removal

https://github.com/stevewongv/dsc-pytorch

Direction-aware Spatial Context Features for Shadow Detection and Removal

https://github.com/sulam-group/learned-proximal-networks

End-to-end reconstruction meets data-driven regularization for inverse problems

https://github.com/ucsd-dsc-arts/dsc160-final-mjisthegoat

Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network

https://github.com/umngangaliqiu/dnn4gnetworking

Real-time Power System State Estimation and Forecasting via Deep Neural Networks

https://github.com/vinits5/PointNetLK

PointNetLK: Robust & Efficient Point Cloud Registration using PointNet

https://github.com/vinits5/learning3d

PointNetLK: Robust & Efficient Point Cloud Registration using PointNet

https://github.com/wkhademi/ImageEnhancement

Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data

https://github.com/wy1iu/OPT

Orthogonal Over-Parameterized Training

https://github.com/xsxjtu/SCSC-PNN

Deep Convolutional Sparse Coding Network for Pansharpening with Guidance of Side Information

https://github.com/xuduo35/InstructPix2Pix

InstructPix2Pix: Learning to Follow Image Editing Instructions

https://github.com/xuhangc/Mask-ShadowGAN-Reimplementation

Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data

https://github.com/xw-hu/DSC

Direction-aware Spatial Context Features for Shadow Detection and Removal

https://github.com/xw-hu/Mask-ShadowGAN

Mask-ShadowGAN: Learning to Remove Shadows from Unpaired Data

https://github.com/yangyucheng000/Paper-2/tree/main/cns

CNSNet: A Cleanness-Navigated-Shadow Network for Shadow Removal

https://github.com/yhao-z/Learned-Low-Rank

T2LR-Net: An unrolling network learning transformed tensor low-rank prior for dynamic MR image reconstruction

https://github.com/yumingj/GroupDiff

GroupDiff: Diffusion-based Group Portrait Editing

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