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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/maxwrf/neural-style-transfer
https://github.com/mayank-17/Project-Image-Restoration-using-SRCNN
https://github.com/mayorquinmachines/YogAI
https://github.com/mayuelala/followyourcanvas
Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free Videos
https://github.com/mayukh18/Hybrid-Style-Siamese-Network
Hybrid Style Siamese Network: Incorporating style loss in complementary apparels retrieval
https://github.com/maz0318/nlpSummerCamp2019
https://github.com/mbzuai-nlp/artst
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/mbzuai-nlp/sttatts
SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing
https://github.com/mbzuai-oryx/unimed-clip
https://github.com/mdt48/semantic-segmentation-pytorch
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/med-seg/kidney
https://github.com/med-seg/kidney-mc
https://github.com/medchaabane/static_objects_geolocalization
End-to-end Learning Improves Static Object Geo-localization in Monocular Video
https://github.com/mediatek-neuropilot/mai22-real-time-video-sr
Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency
https://github.com/meet-minimalist/A-Neural-Algorithm-of-Artistic-Style-Paper-Implementation
https://github.com/megapose6d/megapose6d
MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare
https://github.com/meghshukla/MPII-Human-Pose-Visualization
Bayesian Uncertainty and Expected Gradient Length -- Regression: Two Sides Of The Same Coin?
https://github.com/megvii-research/basecls/tree/main/zoo/public/hrnet
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/megvii-research/conr
https://github.com/megvii-research/ijcai2023-conr
https://github.com/megvii-research/tlsc
https://github.com/mehdibnc/Cycle-GAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mehdidc/any2any
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mehtadushy/SelecSLS-Pytorch
XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera
https://github.com/melgor/pyface
UMDFaces: An Annotated Face Dataset for Training Deep Networks
https://github.com/mengweiren/segmentation-renormalized-harmonization
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mengyingfei/pose-3d-pytorch-ros
Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach
https://github.com/metrics-lab/st-fmri
Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition
https://github.com/mgolnezhad/openpose
https://github.com/mhruz/POTR
https://github.com/mhw32/contrastive-ring-public
Conditional Negative Sampling for Contrastive Learning of Visual Representations
https://github.com/mialbro/PointFusion
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
https://github.com/mialbro/pytorch_pointfusion
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
https://github.com/miaohua1982/simple_fasterrcnn_pytorch
https://github.com/mic-dkfz/medicaldetectiontoolkit
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.