Papers with Code 아카이브

3D Absolute Human Pose Estimation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 4
평가표: 3
보존된 평가 기록: 6

This task aims to solve absolute (camera-centric not root-relative) 3D human pose estimation.

<span style="color:grey; opacity: 0.6">( Image credit: RootNet )</span>

코드

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

https://github.com/bw2color/bw2color

XGBoost: A Scalable Tree Boosting System

https://github.com/cardboard-q/pifuhd_demo_model_test

PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization

https://github.com/chenguolin/DiffSplat

SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video Diffusion

https://github.com/code-implementation1/Code3/tree/main/ESRGAN

Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

https://github.com/code-implementation1/Code6/tree/main/ras

Recurrent Back-Projection Network for Video Super-Resolution

https://github.com/code-implementation1/Code7/tree/main/RefineNet

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

https://github.com/code-implementation1/Code9/tree/main/EDSR

BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

https://github.com/coulsonlee/dy-dca-eccv2024

Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting

https://github.com/cscss/DBVSR

Deep Blind Video Super-resolution

https://github.com/cviaai/PSF-GAN-ESTIMATION

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/dalexanderch/CFD

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/deepak112/Keras-SRGAN

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

https://github.com/djsinghnegi/SRINImageEnhancemrntGAN

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

https://github.com/doantienthongbku/ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/dokyeongK/Pytorch_SRCNN

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/dokyeongK/Single-Image-Super-Resolution-Reimplemenation

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/drhdr-user/drhdr

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks

https://github.com/eriklindernoren/PyTorch-GAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/facebookresearch/multiface

MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement

https://github.com/faheinrich/moon_pose_estimation_setup

Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image

https://github.com/faheinrich/moon_pose_with_detectron2

Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image

https://github.com/fenghansen/ESRGAN-Keras

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/fengwang/subpixel_conv2d

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

https://github.com/ferseiti/reproducibility

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/final-0/Real-ESRGAN

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/final-0/Real-ESRGAN-bicubic

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

https://github.com/fourseaforfriend/waifu2x

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/gchb2012/VQA

Let's Transfer Transformations of Shared Semantic Representations

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

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/gongzix/neuroclips

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

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

Image Super-Resolution Using Deep Convolutional Networks

https://github.com/gs18113/ESPCN-TensorFlow2

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

https://github.com/heartyguy/AI-AngryBird-Eagle-Wing

XGBoost: A Scalable Tree Boosting System

https://github.com/hiyaroy12/multitask_learning

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

https://github.com/hugozanini/realtime-semantic-segmentation

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

https://github.com/idealo/image-super-resolution

ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks

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