Domain enhanced arbitrary image style transfer via contrastive learning Y Zhang, F Tang, W Dong, H Huang, C Ma, TY Lee, C Xu ACM SIGGRAPH 2022 Conference Proceedings, 12:1-12:8, 2022 | 47 | 2022 |
Inversion-Based Style Transfer With Diffusion Models Y Zhang, N Huang, F Tang, H Huang, C Ma, W Dong, C Xu IEEE/CVF Conference on Computer Vision and Pattern Recognition, 10146-10156, 2023 | 22* | 2023 |
Diffstyler: Controllable dual diffusion for text-driven image stylization N Huang, Y Zhang, F Tang, C Ma, H Huang, Y Zhang, W Dong, C Xu arXiv preprint arXiv:2211.10682, 2022 | 8 | 2022 |
ProSpect: Expanded Conditioning for the Personalization of Attribute-aware Image Generation Y Zhang, W Dong, F Tang, N Huang, H Huang, C Ma, TY Lee, O Deussen, ... arXiv preprint arXiv:2305.16225, 2023 | 3 | 2023 |
Portrait map art generation by asymmetric Image-to-Image translation Y Zhang, F Tang, W Dong, TNH Le, C Xu, TY Lee Leonardo 56 (1), 28-36, 2023 | 2 | 2023 |
Style-A-Video: Agile Diffusion for Arbitrary Text-based Video Style Transfer N Huang, Y Zhang, W Dong arXiv preprint arXiv:2305.05464, 2023 | | 2023 |
A Unified Arbitrary Style Transfer Framework via Adaptive Contrastive Learning Y Zhang, F Tang, W Dong, H Huang, C Ma, TY Lee, C Xu ACM Transactions on Graphics, 2023 | | 2023 |
Quantification of Artist Representativity within an Art Movement Y Zhang, F Tang, W Dong, C Xu 2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 1-6, 2022 | | 2022 |