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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mindspore-ai/models/tree/master/research/cv/fairmot
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/PolarizedSelfAttention.py
Polarized Self-Attention: Towards High-quality Pixel-wise Regression
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/attention/TripletAttention.py
https://github.com/mindspore-courses/External-Attention-MindSpore/blob/main/model/conv/DynamicConv.py
https://github.com/mindspore-courses/heads-on-mindspore/tree/main/3-neural_style
https://github.com/mindspore-courses/heads-on-mindspore/tree/main/4-neural_poet_RNN
A Critical Review of Recurrent Neural Networks for Sequence Learning
https://github.com/mindspore-courses/heads-on-mindspore/tree/main/5-image_caption
https://github.com/mindspore-lab/mindone
https://github.com/mindspore-lab/mindone/blob/master/examples/stable_diffusion_v2/T2I-Adapter.md
https://github.com/mindspore-lab/mindone/tree/master/examples/svd
Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
https://github.com/mingyuanzhou/sid
Long and Short Guidance in Score identity Distillation for One-Step Text-to-Image Generation
https://github.com/minhmanho/deep_preset
Deep Preset: Blending and Retouching Photos with Color Style Transfer
https://github.com/mirthai/csa-net
https://github.com/mirzaevinom/data_science_bowl_2018
https://github.com/misuy/misuy_style_transfer_bot
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mithun-bharadwaj/Neural_Style_Transfer
https://github.com/mitmul/deeppose
https://github.com/mjdietzx/SimGAN
Learning from Simulated and Unsupervised Images through Adversarial Training
https://github.com/mks0601/TF-SimpleHumanPose
https://github.com/mkshing/prompt-plus-pytorch
P+: Extended Textual Conditioning in Text-to-Image Generation
https://github.com/mkshing/svdiff-pytorch
https://github.com/ml-gsai/concat-id
Concat-ID: Towards Universal Identity-Preserving Video Synthesis
https://github.com/ml-research/i2p
https://github.com/mlh-fellowship/neuro-art
https://github.com/mlvc-lab/CycleGan_pytorch
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mmakiuchi/multimodal_emotion_recognition
AUTOVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
https://github.com/mnicnc404/CartoonGan-tensorflow
https://github.com/modestyachts/imagenet-testbed
https://github.com/mohaEs/Train-Predict-Landmarks-by-flat-net
Automatic vocal tract landmark localization from midsagittal MRI data
https://github.com/mohammadreyaz/openposered
https://github.com/mohammadreyaz/pose
https://github.com/mohanliu/HRnet-semantic-segmentation-exp
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/mohsenzand/reschunk
Multiscale Residual Learning of Graph Convolutional Sequence Chunks for Human Motion Prediction
https://github.com/monniert/unicorn
https://github.com/mori97/CycleGAN-chainer
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.