https://github.com/alexjc/neural-enhance
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/alexmotogna/attngan
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/alexmotogna/generatorapi
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
https://github.com/alexquach/cycleGAN
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/algonomicon/a-neural-algorithm-of-artistic-style
https://github.com/ali-vilab/FlashFace
FlashFace: Human Image Personalization with High-fidelity Identity Preservation
https://github.com/ali-vilab/VGen
Composer: Creative and Controllable Image Synthesis with Composable Conditions
https://github.com/ali-vilab/i2vgen-xl
Composer: Creative and Controllable Image Synthesis with Composable Conditions
https://github.com/ali-vilab/vace
https://github.com/ali-vilab/videocomposer
Composer: Creative and Controllable Image Synthesis with Composable Conditions
https://github.com/aliabigdeli/nnenum
Verification of Deep Convolutional Neural Networks Using ImageStars
https://github.com/aliaksandrsiarohin/mem-transfer
How to Make an Image More Memorable? A Deep Style Transfer Approach
https://github.com/alibaba-yuanjing-aigclab/vivid
https://github.com/alibaba/EasyCV
https://github.com/alibaba/EasyNLP/tree/master/examples/text2image_generation
https://github.com/alibaba/graph-gpt
https://github.com/alililia/ascend_ESRGAN
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/alililia/ascend_HRNetW48_cls
Deep High-Resolution Representation Learning for Visual Recognition
https://github.com/alililia/ascend_RefineNet
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
https://github.com/alililia/ascend_maskrcnn_mobilenetv1
https://github.com/alililia/gpu_maskrcnn_mobilenetv1
https://github.com/alililia/vision/tree/main/CycleGAN-MS
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/alimohammadiamirhossein/cora
Cora: Correspondence-aware image editing using few step diffusion
https://github.com/alinstein/Modify-image-by-text
StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
https://github.com/alishdipani/Neural-Style-Transfer-Audio
https://github.com/aliutkus/speechmetrics
MOSNet: Deep Learning based Objective Assessment for Voice Conversion
https://github.com/aliyun/Self-Evolving-Keypoint-Demo
https://github.com/allenai/satlas-super-resolution
ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks
https://github.com/alterzero/DBPN-Pytorch
https://github.com/alterzero/RBPN-PyTorch
Recurrent Back-Projection Network for Video Super-Resolution
https://github.com/alterzero/STARnet
https://github.com/alvinwan/shiftresnet-cifar
Shift: A Zero FLOP, Zero Parameter Alternative to Spatial Convolutions
https://github.com/am-sirdaniel/Image-Captioning-Model
https://github.com/amakadia/svd_for_pose
https://github.com/amanshenoy/image-super-resolution
https://github.com/amazingyyc/Brouhaha
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.