https://github.com/0jason000/CLIFF
CLIFF: Carrying Location Information in Full Frames into Human Pose and Shape Estimation
Papers with Code 아카이브
1 Image, 2*2 Stitchi
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/101vinayak/Neural-Style-Transfer
https://github.com/1082-datascience/finalproject-finalproject-1082ds_group3
https://github.com/11aditya11/Neural_Style_Transfer
https://github.com/123972/Deep-Learning-Final-Project
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
https://github.com/15517965908/keras-DBPN
https://github.com/163GitHub/AI
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/1716757342/mmsr
SymFormer: End-to-end symbolic regression using transformer-based architecture
https://github.com/1996scarlet/dense-head-pose-estimation
https://github.com/1adrianb/2D-and-3D-face-alignment
https://github.com/1adrianb/binary-face-alignment
https://github.com/1adrianb/binary-human-pose-estimation
https://github.com/1adrianb/face-alignment-training
https://github.com/1zgh/st-gcn
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/20151001860/Real_ESRGAN_paddle
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
https://github.com/2023-MindSpore-1/ms-code-134
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-15/tree/main/dscnn
https://github.com/2023-MindSpore-1/ms-code-158
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/AlphaPose
AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Time
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/ArbitraryStyleTransfer
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/ArtTrack
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/adelaide_ea
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
https://github.com/2023-MindSpore-1/ms-code-162
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-168
Utilizing Self-supervised Representations for MOS Prediction
https://github.com/2023-MindSpore-1/ms-code-184
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/2023-MindSpore-1/ms-code-199
https://github.com/2023-MindSpore-1/ms-code-201
https://github.com/2023-MindSpore-1/ms-code-207
https://github.com/2023-MindSpore-1/ms-code-208
https://github.com/2023-MindSpore-1/ms-code-210/tree/main/DBPN
https://github.com/2023-MindSpore-1/ms-code-210/tree/main/DDM
https://github.com/2023-MindSpore-1/ms-code-211/tree/main/detr
https://github.com/2023-MindSpore-1/ms-code-213/tree/main/ESRGAN
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HMR
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/2023-MindSpore-1/ms-code-214/tree/main/HRNetW48_seg
High-Resolution Representations for Labeling Pixels and Regions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.