Papers we've found interesting:

Original NST Paper: https://arxiv.org/pdf/1508.06576.pdf

Tutorial with VGG19: https://pytorch.org/tutorials/advanced/neural_style_tutorial.html

Finetuning models: https://pytorch.org/tutorials/beginner/finetuning_torchvision_models_tutorial.html

Article on further NST research using different feature identification: https://ieeexplore-ieee-org.proxy.lib.duke.edu/document/8816670

Improving NST results: https://www.sciencedirect.com/science/article/pii/S1077314221000473

Stretch goal: https://paperswithcode.com/paper/instance-normalization-the-missing-ingredient

Quantitative NST analysis: https://reader.elsevier.com/reader/sd/pii/S1077314221000473?token=AF1BA6058A6C016ACD1C017E6008CF94D1FE728547B53B5713641C9308D0EEEC817D9977B3E638AF94D368143914AAE0&originRegion=us-east-1&originCreation=20210426030038

• Uses https://arxiv.org/pdf/1409.1556.pdf
• Uses https://arxiv.org/pdf/1612.04337.pdf
• Color histogram help: https://www.pyimagesearch.com/2014/07/14/3-ways-compare-histograms-using-opencv-python/