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코드

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

https://github.com/michael13162/DoodleGAN

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

https://github.com/michalgeyer/pnp-diffusers

Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation

https://github.com/mickan123/CycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/microsoft/art

MosAIc: Finding Artistic Connections across Culture with Conditional Image Retrieval

https://github.com/microsoft/visual-chatgpt

High-Resolution Image Synthesis with Latent Diffusion Models

https://github.com/microsoft/vq-diffusion

Vector Quantized Diffusion Model for Text-to-Image Synthesis

https://github.com/mid-push/irwgan

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/midas-research/text2facegan

Text2FaceGAN: Face Generation from Fine Grained Textual Descriptions

https://github.com/midm/FastPhotoStyle

A Closed-form Solution to Photorealistic Image Stylization

https://github.com/miguelCalado/prompt-to-prompt-tensorflow

Prompt-to-Prompt Image Editing with Cross Attention Control

https://github.com/mikecheninoulu/Emotional-gesture-papers

Survey on Emotional Body Gesture Recognition

https://github.com/mikepatel/Text-2-Image-GAN

Generative Adversarial Text to Image Synthesis

https://github.com/mikeshihyaolin/pose-hg-3d-preprocessing

Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach

https://github.com/milmor/latent-diffusion-transformer

High-Resolution Image Synthesis with Latent Diffusion Models

https://github.com/milmor/perceptual-losses-neural-style

Perceptual Losses for Real-Time Style Transfer and Super-Resolution

https://github.com/minar09/MGN

Multi-Garment Net: Learning to Dress 3D People from Images

https://github.com/minar09/MGN-Py3

Multi-Garment Net: Learning to Dress 3D People from Images

https://github.com/minar09/MultiGarmentNetworkPython3

Multi-Garment Net: Learning to Dress 3D People from Images

https://github.com/minar09/acgpn

Towards Photo-Realistic Virtual Try-On by Adaptively Generating$\leftrightarrow$Preserving Image Content

https://github.com/minar09/cp-vton-plus

https://github.com/mindspore-ai/contrib/tree/master/intern/pixelshuffle1d

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network

https://github.com/mindspore-ai/models/blob/master/research/cv/StackedHourglass

Stacked Hourglass Networks for Human Pose Estimation

https://github.com/mindspore-ai/models/blob/master/research/cv/simple_baselines/

Simple Baselines for Human Pose Estimation and Tracking

https://github.com/mindspore-ai/models/tree/master/official/cv/maskrcnn

Mask R-CNN

https://github.com/mindspore-ai/models/tree/master/official/cv/openpose

Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

https://github.com/mindspore-ai/models/tree/master/official/cv/simple_pose

Simple Baselines for Human Pose Estimation and Tracking

https://github.com/mindspore-ai/models/tree/master/official/cv/srcnn

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/mindspore-ai/models/tree/master/research/cv/AlphaPose

RMPE: Regional Multi-person Pose Estimation

https://github.com/mindspore-ai/models/tree/master/research/cv/ArbitraryStyleTransfer

Exploring the structure of a real-time, arbitrary neural artistic stylization network

https://github.com/mindspore-ai/models/tree/master/research/cv/ArtTrack

ArtTrack: Articulated Multi-person Tracking in the Wild

https://github.com/mindspore-ai/models/tree/master/research/cv/CycleGAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/mindspore-ai/models/tree/master/research/cv/ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/mindspore-ai/models/tree/master/research/cv/HRNetW48_cls

Deep High-Resolution Representation Learning for Visual Recognition

https://github.com/mindspore-ai/models/tree/master/research/cv/PAMTRI

PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data

https://github.com/mindspore-ai/models/tree/master/research/cv/RefineNet

RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation

https://github.com/mindspore-ai/models/tree/master/research/cv/adelaide_ea

Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells

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