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Virtual try-on focuses on adjusting the given clothes to fit a specific person seamlessly while avoiding any distortion of the patterns and textures of the garment.
Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2014) Generative adversarial nets. Advances in neural information processing systems 27
2014
Earlier work this paper cites.
Long J, Shelhamer E, Darrell T (2015) Fully convolutional networks for semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3431–3440
2015
Earlier work this paper cites.
Sohl-Dickstein J, Weiss E, Maheswaranathan N, Ganguli S (2015) Deep unsupervised learning using nonequilibrium thermodynamics. In: International conference on machine learning, PMLR, pp 2256–2265
2015
Earlier work this paper cites.
Gulrajani I, Ahmed F, Arjovsky M, Dumoulin V, Courville AC (2017) Improved training of wasserstein gans. Advances in neural information processing systems 30
2017
Earlier work this paper cites.
Loshchilov I, Hutter F (2017) Decoupled weight decay regularization. arXiv preprint arXiv:171105101
2017
Earlier work this paper cites.
Zhu S, Urtasun R, Fidler S, Lin D, Change Loy C (2017) Be your own prada: Fashion synthesis with structural coherence. In: Proceedings of the IEEE international conference on computer vision, pp 1680–1688
2017
Earlier work this paper cites.
Güler RA, Neverova N, Kokkinos I (2018) Densepose: Dense human pose estimation in the wild. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7297–7306
2018
Earlier work this paper cites.
Han X, Wu Z, Wu Z, Yu R, Davis LS (2018) Viton: An image-based virtual try-on network. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7543–7552
2018
Earlier work this paper cites.
Miyato T, Kataoka T, Koyama M, Yoshida Y (2018) Spectral normalization for generative adversarial networks. arXiv preprint arXiv:180205957
2018
Earlier work this paper cites.
Wang B, Zheng H, Liang X, Chen Y, Lin L, Yang M (2018) Toward characteristic-preserving image-based virtual try-on network. In: Proceedings of the European conference on computer vision (ECCV), pp 589–604
2018
Earlier work this paper cites.
Fu J, Liu J, Tian H, Li Y, Bao Y, Fang Z, Lu H (2019) Dual attention network for scene segmentation. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 3146–3154
2019
Earlier work this paper cites.
Han X, Hu X, Huang W, Scott MR (2019) Clothflow: A flow-based model for clothed person generation. In: Proceedings of the IEEE/CVF international conference on computer vision, pp 10471–10480
2019
Earlier work this paper cites.
Li L, Bao J, Yang H, Chen D, Wen F (2019) Faceshifter: Towards high fidelity and occlusion aware face swapping. arXiv preprint arXiv:191213457
2019
Earlier work this paper cites.
Zheng N, Song X, Chen Z, Hu L, Cao D, Nie L (2019) Virtually trying on new clothing with arbitrary poses. In: Proceedings of the 27th ACM international conference on multimedia, pp 266–274
2019
Earlier work this paper cites.
Ho J, Jain A, Abbeel P (2020) Denoising diffusion probabilistic models. Advances in neural information processing systems 33:6840–6851
2020
Earlier work this paper cites.
Issenhuth T, Mary J, Calauzenes C (2020) Do not mask what you do not need to mask: a parser-free virtual try-on. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XX 16, Springer, pp 619–635
2020
Earlier work this paper cites.
Karras T, Laine S, Aittala M, Hellsten J, Lehtinen J, Aila T (2020) Analyzing and improving the image quality of stylegan. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 8110–8119
2020
Earlier work this paper cites.
Minar MR, Tuan TT, Ahn H, Rosin P, Lai YK (2020) Cp-vton+: Clothing shape and texture preserving image-based virtual try-on. In: CVPR Workshops, vol 3, pp 10–14
2020
Cited alongside, same era.
Song J, Meng C, Ermon S (2020) Denoising diffusion implicit models. arXiv preprint arXiv:201002502
2020
Cited alongside, same era.
Yang H, Zhang R, Guo X, Liu W, Zuo W, Luo P (2020) Towards photo-realistic virtual try-on by adaptively generating-preserving image content. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 7850–7859
2020
Cited alongside, same era.
Choi S, Park S, Lee M, Choo J (2021) Viton-hd: High-resolution virtual try-on via misalignment-aware normalization. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 14131–14140
2021
Cited alongside, same era.
Saharia C, Chan W, Saxena S, Li L, Whang J, Denton EL, Ghasemipour K, Gontijo Lopes R, Karagol Ayan B, Salimans T, et al. (2022) Photorealistic text-to-image diffusion models with deep language understanding. Advances in Neural Information Processing Systems 35:36479–36494
2022
Later among the works it cites.
Wang Q, Liu L, Hua M, He Q, Zhu P, Cao B, Hu Q (2022) Hs-diffusion: Learning a semantic-guided diffusion model for head swapping. arXiv preprint arXiv:221206458
2022
Later among the works it cites.
Avrahami O, Fried O, Lischinski D (2023) Blended latent diffusion. ACM Transactions on Graphics (TOG) 42(4):1–11
2023
Later among the works it cites.
Baldrati A, Morelli D, Cartella G, Cornia M, Bertini M, Cucchiara R (2023) Multimodal garment designer: Human-centric latent diffusion models for fashion image editing. arXiv preprint arXiv:230402051
2023
Later among the works it cites.
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2021
Cited alongside, same era.
Lewis KM, Varadharajan S, Kemelmacher-Shlizerman I (2021) Tryongan: Body-aware try-on via layered interpolation. ACM Transactions on Graphics (TOG) 40(4):1–10
2021
Cited alongside, same era.
Nichol A, Dhariwal P, Ramesh A, Shyam P, Mishkin P, McGrew B, Sutskever I, Chen M (2021) Glide: Towards photorealistic image generation and editing with text-guided diffusion models. arXiv preprint arXiv:211210741
2021
Cited alongside, same era.
Bai S, Zhou H, Li Z, Zhou C, Yang H (2022) Single stage virtual try-on via deformable attention flows. In: European Conference on Computer Vision, Springer, pp 409–425
2022
Cited alongside, same era.
Gal R, Alaluf Y, Atzmon Y, Patashnik O, Bermano AH, Chechik G, Cohen-Or D (2022) An image is worth one word: Personalizing text-to-image generation using textual inversion. arXiv preprint arXiv:220801618
2022
Cited alongside, same era.
He S, Song YZ, Xiang T (2022) Style-based global appearance flow for virtual try-on. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp 3470–3479
2022
Cited alongside, same era.
Ho J, Salimans T (2022) Classifier-free diffusion guidance. arXiv preprint arXiv:220712598
2022
Cited alongside, same era.
Lee S, Gu G, Park S, Choi S, Choo J (2022) High-resolution virtual try-on with misalignment and occlusion-handled conditions. In: European Conference on Computer Vision, Springer, pp 204–219
2022
Cited alongside, same era.
Bhunia AK, Khan S, Cholakkal H, Anwer RM, Laaksonen J, Shah M, Khan FS (2023) Person image synthesis via denoising diffusion model. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp 5968–5976
2023
Later among the works it cites.
Cui A, Mahajan J, Shah V, Gomathinayagam P, Lazebnik S (2023) Street tryon: Learning in-the-wild virtual try-on from unpaired person images. arXiv preprint arXiv:231116094
2023
Later among the works it cites.
Gou J, Sun S, Zhang J, Si J, Qian C, Zhang L (2023) Taming the power of diffusion models for high-quality virtual try-on with appearance flow. arXiv preprint arXiv:230806101
2023
Later among the works it cites.
Kim J, Gu G, Park M, Park S, Choo J (2023) Stableviton: Learning semantic correspondence with latent diffusion model for virtual try-on. arXiv preprint arXiv:231201725
2023
Later among the works it cites.
Morelli D, Baldrati A, Cartella G, Cornia M, Bertini M, Cucchiara R (2023) Ladi-vton: Latent diffusion textual-inversion enhanced virtual try-on. arXiv preprint arXiv:230513501
2023
Later among the works it cites.
Mou C, Wang X, Xie L, Zhang J, Qi Z, Shan Y, Qie X (2023) T2i-adapter: Learning adapters to dig out more controllable ability for text-to-image diffusion models. arXiv preprint arXiv:230208453
2023
Later among the works it cites.
Shi J, Xiong W, Lin Z, Jung HJ (2023) Instantbooth: Personalized text-to-image generation without test-time finetuning. arXiv preprint arXiv:230403411
2023
Later among the works it cites.
Wei Y, Zhang Y, Ji Z, Bai J, Zhang L, Zuo W (2023) Elite: Encoding visual concepts into textual embeddings for customized text-to-image generation. arXiv preprint arXiv:230213848
2023
Later among the works it cites.
Xie Z, Huang Z, Dong X, Zhao F, Dong H, Zhang X, Zhu F, Liang X (2023) Gp-vton: Towards general purpose virtual try-on via collaborative local-flow global-parsing learning. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp 23550–23559
2023
Later among the works it cites.
Yang B, Gu S, Zhang B, Zhang T, Chen X, Sun X, Chen D, Wen F (2023) Paint by example: Exemplar-based image editing with diffusion models. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp 18381–18391
2023
Later among the works it cites.
Zhang L, Rao A, Agrawala M (2023) Adding conditional control to text-to-image diffusion models. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp 3836–3847
2023
Later among the works it cites.
Corneanu C, Gadde R, Martinez AM (2024) Latentpaint: Image inpainting in latent space with diffusion models. In: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp 4334–4343
2024
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