no code implementations • 22 Sep 2023 • Doris Antensteiner, Marah Halawa, Asra Aslam, Ivaxi Sheth, Sachini Herath, Ziqi Huang, Sunnie S. Y. Kim, Aparna Akula, Xin Wang
In this paper, we present the details of Women in Computer Vision Workshop - WiCV 2023, organized alongside the hybrid CVPR 2023 in Vancouver, Canada.
1 code implementation • 20 Sep 2023 • Chenyang Si, Ziqi Huang, Yuming Jiang, Ziwei Liu
In this paper, we uncover the untapped potential of diffusion U-Net, which serves as a "free lunch" that substantially improves the generation quality on the fly.
no code implementations • 2 Aug 2023 • Zhipeng Tan, Baifan Zhou, Zhuoxun Zheng, Ognjen Savkovic, Ziqi Huang, Irlan-Grangel Gonzalez, Ahmet Soylu, Evgeny Kharlamov
Recently there has been a series of studies in knowledge graph embedding (KGE), which attempts to learn the embeddings of the entities and relations as numerical vectors and mathematical mappings via machine learning (ML).
1 code implementation • CVPR 2023 • Ziqi Huang, Kelvin C. K. Chan, Yuming Jiang, Ziwei Liu
In this work, we present Collaborative Diffusion, where pre-trained uni-modal diffusion models collaborate to achieve multi-modal face generation and editing without re-training.
2 code implementations • 23 Mar 2023 • Ziqi Huang, Tianxing Wu, Yuming Jiang, Kelvin C. K. Chan, Ziwei Liu
Specifically, we propose a novel relation-steering contrastive learning scheme to impose two critical properties of the relation prompt: 1) The relation prompt should capture the interaction between objects, enforced by the preposition prior.
no code implementations • 14 Mar 2022 • Ziqi Huang, Li Lin, Pujin Cheng, Kai Pan, Xiaoying Tang
Furthermore, with only 5% paired data, the proposed DS3-Net achieves competitive performance with state-of-theart image translation methods utilizing 100% paired data, delivering an average SSIM of 0. 8947 and an average PSNR of 23. 60.
no code implementations • 9 Mar 2022 • Ziqi Huang, Li Lin, Pujin Cheng, Linkai Peng, Xiaoying Tang
As such, it is clinically meaningful to develop a method to synthesize unavailable modalities which can also be used as additional inputs to downstream tasks (e. g., brain tumor segmentation) for performance enhancing.
1 code implementation • 13 Jan 2022 • Linkai Peng, Li Lin, Pujin Cheng, Ziqi Huang, Xiaoying Tang
The two models use labeled data (together with the corresponding transferred images) for supervised learning and perform collaborative consistency learning on unlabeled data.
1 code implementation • ICCV 2021 • Yuming Jiang, Ziqi Huang, Xingang Pan, Chen Change Loy, Ziwei Liu
In this work, we propose Talk-to-Edit, an interactive facial editing framework that performs fine-grained attribute manipulation through dialog between the user and the system.
Ranked #1 on
Fine-Grained Facial Editing
on CelebA-Dialog