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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/mousecpn/Domain-Generalization-via-Image-Stylization
Frustratingly Simple Domain Generalization via Image Stylization
https://github.com/mousecpn/Joint-Bilateral-Learning
Joint Bilateral Learning for Real-time Universal Photorealistic Style Transfer
https://github.com/mowshon/lipsync
A Lip Sync Expert Is All You Need for Speech to Lip Generation In The Wild
https://github.com/mpaepper/stablediffusion_magicmix
https://github.com/mrStasSmirnoff/GAN_basics
https://github.com/mramly/CairoMent
AraBERT: Transformer-based Model for Arabic Language Understanding
https://github.com/mrlibw/Lightweight-Manipulation
Lightweight Generative Adversarial Networks for Text-Guided Image Manipulation
https://github.com/mronta/CycleGAN-in-Keras
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/mseg-dataset/mseg-semantic
High-Resolution Representations for Labeling Pixels and Regions
https://github.com/msfasha/Arabic-NLP
AraBERT: Transformer-based Model for Arabic Language Understanding
https://github.com/mshaikh2/GANs_Comparison
https://github.com/mshn2000/PointFusion
PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation
https://github.com/mstfakts/building-detection-maskrcnn
https://github.com/msurtsukov/neural-ode
https://github.com/mszpc/StyTR-2-mindspore
https://github.com/mtorabirad/PricePrediction
https://github.com/muelea/tuch
https://github.com/muhdhuz/Audio_NeuralStyle
https://github.com/mukul1093/Image-Super-Resolution
https://github.com/mukulanandchas/ART-GENERATION-USING-NEURAL-STYLE-TRANSFER
https://github.com/multimodallearning/pytorch-mask-rcnn
https://github.com/murdockhou/Single-Stage-Multi-person-Pose-Machines
https://github.com/murdockhou/lightweight_openpose
Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose
https://github.com/muriloime/awesome-stars
https://github.com/murrman95/INF573Project2018
Accurate Image Super-Resolution Using Very Deep Convolutional Networks
https://github.com/murufeng/FUIR
https://github.com/muyistarsky/MaskRCNN
https://github.com/mv-lab/InstructIR
InstructPix2Pix: Learning to Follow Image Editing Instructions
https://github.com/mv-lab/swin2sr
https://github.com/mvenouziou/Project_Style_Transfer
https://github.com/myscience/open-genie
https://github.com/n1243645679976/svsnet
SVSNet: An End-to-end Speaker Voice Similarity Assessment Model
https://github.com/nabarunbaruaAIML/ATCC_Yolov5
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/nafiuny/ICRCycleGAN-VC
Voice Conversion from Non-parallel Corpora Using Variational Auto-encoder
https://github.com/nagadomi/waifu2x
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.