2D Human Pose Estimation
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 6
- 평가표
- 10
- 보존된 평가 기록
- 47
What is Human Pose Estimation? Human pose estimation is the process of estimating the configuration of the body (pose) from a single, typically monocular, image. Background. Human pose estimation is one of the key problems in computer vision that has been studied for well over 15 years. The reason for its importance is the abundance of applications that can benefit from such a technology. For example, human pose estimation allows for higher-level reasoning in the context of human-computer interaction and activity recognition; it is also one of the basic building blocks for marker-less motion capture (MoCap) technology. MoCap technology is useful for applications ranging from character animation to clinical analysis of gait pathologies.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/RyotaImai/-Keras-Image2StyleGAN-
https://github.com/S-aiueo32/dni-demo
Deep Network Interpolation for Continuous Imagery Effect Transition
https://github.com/S-aiueo32/srntt-pytorch
https://github.com/SHAHBAZSIDDIQI/DataScience
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/SJHNJU/VDSR
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/Saadbutt321/Conversion-of-Pakistan-Sign-Language-into-Text-and-Speech-using-OpenPose-and-Machine-Learning
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/Saaiheswar/Neural-Style-Transfer
https://github.com/SambhawDrag/XLNet.jl
Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context
https://github.com/Samyu0304/thought-propagation
https://github.com/Santosh-Gupta/Arxiv-Manatee
https://github.com/SarderLab/WSI-cycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/SasCezar/XWikiRE
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
https://github.com/SeonghoBaek/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/ShaoweiSong0718/HigherHRNet-Human-Pose-Estimation
HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation
https://github.com/Shawn-Inspur/Yuan-1.0
Yuan 1.0: Large-Scale Pre-trained Language Model in Zero-Shot and Few-Shot Learning
https://github.com/ShawnWilliams/style_transfer
https://github.com/Shilpil/style-transfer
https://github.com/Shritesh99/100DaysofMLCodeChallenge
https://github.com/Shritesh99/Image_Super_Resolution
https://github.com/Shumway82/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/ShutoAraki/EverybodyDanceNow-Temporal-FaceGAN
https://github.com/SiHaoShen/Convolutional-Neural-Networks
https://github.com/SiddhanthHegde/Custom-Neural-Style-Transfer
https://github.com/SilasHenderson/AI
https://github.com/SilasHenderson/ai_notes
https://github.com/SimeonKraev/Musical-style-transfer-with-cycle-consistent-generative-adversarial-neural-networks
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/SimoneDutto/EDSR
https://github.com/Sobeit-Tim/NuguEyeTest
Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields
https://github.com/SocieteGenevoiseDonnees/FiltersStylesDomains
https://github.com/Sontref/CycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/SreeHarshaNelaturu/Neural-Style-Transfer
https://github.com/Srijha09/Making-Images-Artsy-Neural-Style-Transfer
https://github.com/SudhanshuMishra8826/Style-Transfer-On-Images
https://github.com/SumUpAnalytics/goldsum
Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies
https://github.com/SunJuil-Ty/simplebaselines-mindspore
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.