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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hlzz/DeepMatchVO
Self-Supervised Learning of Depth and Motion Under Photometric Inconsistency
https://github.com/hmatty/stylized-neural-painting
https://github.com/hnmspirit/malaria_centernet
https://github.com/hoanguyen81190/Synopticon-CenterNet
https://github.com/hollygrimm/cyclegan-keras-art-attrs
Instance Normalization: The Missing Ingredient for Fast Stylization
https://github.com/hologerry/AGIS-Net
https://github.com/honzaMaly/cyclegan-style-transfer
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/hordiales/transferencia-estilo-sms
https://github.com/houssemjebari/Fruit-Detection
https://github.com/hrhodin/NeuralSceneDecomposition
https://github.com/hrhodin/UnsupervisedGeometryAwareRepresentationLearning
Unsupervised Geometry-Aware Representation for 3D Human Pose Estimation
https://github.com/hsk9767/open_pose
Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose
https://github.com/hsp-iit/byogg
Bring Your Own Grasp Generator: Leveraging Robot Grasp Generation for Prosthetic Grasping
https://github.com/hthoai/UI2IT
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/huawei-noah/Speech-Backbones/tree/main/Grad-TTS
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
https://github.com/huggingface/diffusers
Versatile Diffusion: Text, Images and Variations All in One Diffusion Model
https://github.com/huggingface/open-muse
Muse: Text-To-Image Generation via Masked Generative Transformers
https://github.com/huggingface/pytorch-image-models
https://github.com/huggingface/transformers
SuperGlue: Learning Feature Matching with Graph Neural Networks
https://github.com/hugozanini/realtime-semantic-segmentation
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/huguyuehuhu/HCN-pytorch
https://github.com/huihuangz/Neural-Style-Transfer-Papers-Code
Automatic Semantic Style Transfer using Deep Convolutional Neural Networks and Soft Masks
https://github.com/hujinsen/pytorch-StarGAN-VC
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/hulianyuyy/adabrowse
Self-Emphasizing Network for Continuous Sign Language Recognition
https://github.com/human-aimachine-art/pytorch-STROTSS-improved
Style Transfer by Relaxed Optimal Transport and Self-Similarity
https://github.com/huochf/StackFLOW
Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
https://github.com/huyz1117/Non_Local_Net_TensorFlow
https://github.com/hw666666666666/MIMO-UNet
Rethinking Coarse-to-Fine Approach in Single Image Deblurring
https://github.com/hx19940102/Image-Captioning
https://github.com/hxixixh/adaflow
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
https://github.com/hxwork/H2ONet_Pytorch
https://github.com/hyeonseobnam/batch-instance-normalization
Batch-Instance Normalization for Adaptively Style-Invariant Neural Networks
https://github.com/hyn2028/llm-cxr
https://github.com/hyperionfalling/lightpose
Rethinking on Multi-Stage Networks for Human Pose Estimation
https://github.com/hyperplane-lab/Generative-3D-Part-Assembly
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.