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코드

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

https://github.com/geopavlakos/object3d

Stacked Hourglass Networks for Human Pose Estimation

https://github.com/geopavlakos/ordinal-pose3d

Stacked Hourglass Networks for Human Pose Estimation

https://github.com/george-gca/sr-pytorch-lightning

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/germain-hug/NRE

Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation

https://github.com/germanjke/StyleTransformerGANs

Multi-style Generative Network for Real-time Transfer

https://github.com/gfjiangly/CenterNet

Objects as Points

https://github.com/gfoxx29/Image-Captioning

Show and Tell: A Neural Image Caption Generator

https://github.com/giannisdaras/multires_textual_inversion

An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion

https://github.com/gidobot/SilhoNet

SilhoNet: An RGB Method for 6D Object Pose Estimation

https://github.com/github-zbx/ST-GCN

Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/gitting-it-right/gaussian_centernet

Objects as Points

https://github.com/gkeng/viton-gan

VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss

https://github.com/gkv856/end2end_auto_voice_conversion

AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss

https://github.com/glebsbrykin/sanet

Arbitrary Style Transfer with Style-Attentional Networks

https://github.com/glouppe/info8010-deep-learning

High-Resolution Image Synthesis with Latent Diffusion Models

https://github.com/gnhdnb/adjustable-real-time-style-transfer

Adjustable Real-time Style Transfer

https://github.com/godspeedcurry/lung-nodule-detection

Mask R-CNN

https://github.com/gogojjh/ESVO_extension

Event-based Stereo Visual Odometry

https://github.com/gokriznastic/torch-style-transfer

A Neural Algorithm of Artistic Style

https://github.com/gongzix/neuroclips

Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models

https://github.com/goodxue/CenterNet

Objects as Points

https://github.com/google-coral/project-posenet

PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model

https://github.com/google-deepmind/graphcast

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

https://github.com/google-research/google-research/tree/master/poem

View-Invariant, Occlusion-Robust Probabilistic Embedding for Human Pose

https://github.com/google-research/sparf

Learning Accurate Dense Correspondences and When to Trust Them

https://github.com/google-research/trecs_image_generation

Text-to-Image Generation Grounded by Fine-Grained User Attention

https://github.com/google/RED

The Little Engine that Could: Regularization by Denoising (RED)

https://github.com/google/samurai

SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collections

https://github.com/gordicaleksa/pytorch-neural-style-transfer

A Neural Algorithm of Artistic Style

https://github.com/gordicaleksa/pytorch-neural-style-transfer-fast

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

https://github.com/gordicaleksa/pytorch-nst-feedforward

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

https://github.com/goutern/PoseEstimation

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

https://github.com/gouthamvgk/SuperGlue_training

SuperGlue: Learning Feature Matching with Graph Neural Networks

https://github.com/gox-ai/hrnet-pose-api

Deep High-Resolution Representation Learning for Human Pose Estimation

https://github.com/gpastal24/ViTPose-Pytorch

ViTPose: Simple Vision Transformer Baselines for Human Pose Estimation

https://github.com/gq-sonofgod/zoom-picture

Image Super-Resolution Using Deep Convolutional Networks

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