• 주제 선정 마인드맵

    • https://drive.google.com/file/d/1T8qoqo42_rT57ebS0RStPDjvXc6CA0r0/view?usp=sharing
  • 반려동물 관련 기사 및 리포트

    • 김미정, "1인 가구 열 집 중 한 집 '반려동물' 키운다", 1코노미뉴스, 2020.03.10, http://www.1conomynews.co.kr/news/articleView.html?idxno=10956
    • 황원경 외 1명, 「2021 한국 반려동물 보고서」, KB금융지주, 2021.03.21, https://www.kbfg.com/kbresearch/report/reportView.do?reportId=2000160
    • 이수빈, "펫셔리, 최고·최상으로 해줄게!…펫부심, 너는 나의 자부심이야!", 한국경제신문, 2021.08.26, https://www.hankyung.com/life/article/2021082615721
    • 이보람, "간직하고 싶은 반려동물과의 추억 화폭에 담아요", 광주일보, 2021.10.15, http://kwangju.co.kr/article.php?aid=1634256000727601314
    • 조가연 외 1명, '성공예감 김방희입니다 인터뷰', KBS NEWS, 2022.02.08, https://news.kbs.co.kr/news/view.do?ncd=5390014
    • 전희윤, “펫케어 시장 260조원 규모로 성장…트렌드 반영한 전략 세워야”, 서울경제, 2022.01.19, https://www.sedaily.com/NewsVIew/260XCNNGBL
    • 이나경, "6조 시장 열린다...반려동물 사업 본격 확장", 아주경제, 2022.01.30, https://www.ajunews.com/view/20220130004404009
    • Reilly Roberts, "Pet Industry Trends, Growth & Statistics in 2022 and Beyond: Unleashing Your Ecommerce Pet Marketing Strategies", COMMON THREAD, 2022.03.07, https://commonthreadco.com/blogs/coachs-corner/pet-industry-trends-growth-ecommerce-marketing
  • 저작권법 관련

    • 김윤명. 인공지능에 의한 저작물 이용 및 창작에 대한 법적 검토와 시사점. 법제연구. 2016; 51 191-239., https://drive.google.com/file/d/1F9T-I5zu-XdIPz-8QEFXrCQG-1pQxtox/view?usp=sharing
  • CartoonGAN 관련

    • Chen et al, CartoonGAN: Generative Adversarial Networks for Photo Cartoonization, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, https://openaccess.thecvf.com/content_cvpr_2018/papers/Chen_CartoonGAN_Generative_Adversarial_CVPR_2018_paper.pdf
    • https://github.com/mnicnc404/CartoonGan-tensorflow
    • https://blog.diyaml.com/teampost/Improving-CartoonGAN/(https://aruie.github.io/2019/11/14/CartoonGAN.html)
    • https://colab.research.google.com/github/TobiasSunderdiek/cartoon-gan/blob/master/CartoonGAN.ipynb#scrollTo=hqBoaA8tSZh8
    • https://jaejunyoo.blogspot.com/2017/03/lsgan-1.html
  • Segmentation 관련

    • Chen et al, Rethinking Atrous Convolution for Semantic Image Segmentation[J]. arXiv: Computer Vision and Pattern Recognition, 2017, https://arxiv.org/pdf/1706.05587.pdf
    • https://github.com/kairess/semantic-segmentation-pytorch
    • https://sualab.github.io/practice/2018/11/23/image-segmentation-deep-learning.html
    • https://pytorch.org/hub/pytorch_vision_deeplabv3_resnet101/
    • https://gaussian37.github.io/vision-segmentation-deeplabv3/
  • Real-ESRGAN 관련

    • Wang et al, Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data, arXiv:Image and Video Processing/Computer Vision and Pattern Recognition, 2021, https://openaccess.thecvf.com/content/ICCV2021W/AIM/papers/Wang_Real-ESRGAN_Training_Real-World_Blind_Super-Resolution_With_Pure_Synthetic_Data_ICCVW_2021_paper.pdf
    • https://github.com/xinntao/Real-ESRGAN
    • https://velog.io/@heaseo/Real-ESRGAN-Training-Real-World-Blind-Super-Resolution-with-Pure-Synthetic-Data-해석