no code implementations • 6 Dec 2023 • Jianjin Xu, Saman Motamed, Praneetha Vaddamanu, Chen Henry Wu, Christian Haene, Jean-Charles Bazin, Fernando de la Torre
Specifically, we insert parallel attention matrices to each cross-attention module in the denoising network, which attends to features extracted from reference images by an identity encoder.
2 code implementations • ICCV 2023 • Saman Motamed, Jianjin Xu, Chen Henry Wu, Fernando de la Torre
By using ~40 reference images, PATMAT creates anchor points in MAT's style module, and tunes the model using the fixed anchors to adapt the model to a new face identity.
no code implementations • 30 Nov 2022 • Jianjin Xu, Zhaoxiang Zhang, Xiaolin Hu
Second, we train image-to-image translation networks on the synthesized datasets, enabling semantic-conditional image synthesis without human annotations.
no code implementations • 11 Jun 2022 • Han Liu, Bingning Wang, Ting Yao, Haijin Liang, Jianjin Xu, Xiaolin Hu
Large-scale pre-trained language models have achieved great success on natural language generation tasks.
1 code implementation • CVPR 2021 • Jianjin Xu, Changxi Zheng
Given a trained GAN and as few as eight semantic annotations, the user is able to generate diverse images subject to a user-provided semantic layout, and control the synthesized image semantics.
2 code implementations • 11 Feb 2021 • Jianjin Xu, Zheyang Xiong, Xiaolin Hu
To ensure temporal inconsistency between the frames of the stylized video, a common approach is to estimate the optic flow of the pixels in the original video and make the generated pixels match the estimated optical flow.