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코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/harshm121/m3l

Multimodal Token Fusion for Vision Transformers

https://github.com/haru-256/pix2pixHD.pytorch

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

https://github.com/harunshimanto/Neural-Style-Transfer-of-Artistic-Style

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hcholab/k-salsa

Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation

https://github.com/hcygeorge/aoi_defect_detection

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hello-world-cc/starGANv1-Pytorch

StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

https://github.com/henriquemeloo/cat-dog-image-classifier

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hero9968/pix2pix-tensorflow

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/hershd23/ObjectLocalizer

Deep Residual Learning for Image Recognition

https://github.com/hieu2906090/deep-learning-in-js

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hmatty/stylized-neural-painting

Stylized Neural Painting

https://github.com/hollance/VGGNet-Metal

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/holstgr-kaust/keras-tutorials

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hongkunsun/paratranscnn

Deep Residual Learning for Image Recognition

https://github.com/hongyi-zhang/Fixup

Deep Residual Learning for Image Recognition

https://github.com/honzaMaly/cyclegan-style-transfer

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/horse007666/ResNet

Deep Residual Learning for Image Recognition

https://github.com/hsd1503/resnet1d

Deep Residual Learning for Image Recognition

https://github.com/hsinyilin19/resnetvae

Deep Residual Learning for Image Recognition

https://github.com/hthoai/UI2IT

Unsupervised Image-to-Image Translation Networks

https://github.com/huawei-noah/Pruning

Co-Evolutionary Compression for Unpaired Image Translation

https://github.com/huggingface/transformers

Visual Instruction Tuning

https://github.com/hujinsen/pytorch-StarGAN-VC

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/humansensinglab/cycle-diffusion

Unifying Diffusion Models' Latent Space, with Applications to CycleDiffusion and Guidance

https://github.com/hustic/TinyImageSet

Deep Residual Learning for Image Recognition

https://github.com/hustvl/sparseinst

Deep Residual Learning for Image Recognition

https://github.com/hwang9u/hum2Guitar

High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

https://github.com/hx19940102/Image-Segmentation-based-on-FCN

Deep Residual Learning for Image Recognition

https://github.com/hycis/TensorGraph

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/hyhchaos/FakePolisher

FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction

https://github.com/hyn2028/llm-cxr

Taming Transformers for High-Resolution Image Synthesis

https://github.com/hysts/pytorch_resnet

Deep Residual Learning for Image Recognition

https://github.com/hysts/pytorch_resnet_preact

Deep Residual Learning for Image Recognition

https://github.com/hytseng0509/DRIT_hr

Diverse Image-to-Image Translation via Disentangled Representations

https://github.com/hz2538/iot_JennyGo

Deep Residual Learning for Image Recognition

https://github.com/iArunava/ResNet

Deep Residual Learning for Image Recognition

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.