no code implementations • ECCV 2020 • Jian Hu, Hongya Tuo, Chao Wang, Lingfeng Qiao, Haowen Zhong, Junchi Yan, Zhongliang Jing, Henry Leung
Previous methods typically match the whole source domain to target domain, which causes negative transfer due to the source-negative classes in source domain that does not exist in target domain.
no code implementations • 17 Mar 2024 • Yuxuan Zhang, Yiren Song, Jinpeng Yu, Han Pan, Zhongliang Jing
Currently, personalized image generation methods mostly require considerable time to finetune and often overfit the concept resulting in generated images that are similar to custom concepts but difficult to edit by prompts.
1 code implementation • 26 Dec 2023 • Yuxuan Zhang, Yiren Song, Jiaming Liu, Rui Wang, Jinpeng Yu, Hao Tang, Huaxia Li, Xu Tang, Yao Hu, Han Pan, Zhongliang Jing
Recent advancements in subject-driven image generation have led to zero-shot generation, yet precise selection and focus on crucial subject representations remain challenging.
1 code implementation • 5 Dec 2022 • Yiren Song, Xuning Shao, Kang Chen, Weidong Zhang, Minzhe Li, Zhongliang Jing
Considerable progress has recently been made in leveraging CLIP (Contrastive Language-Image Pre-Training) models for text-guided image manipulation.
1 code implementation • 1 Dec 2022 • Yu Yuan, Jiaqi Wu, Zhongliang Jing, Henry Leung, Han Pan
In this letter, we present a hybrid model consisting of a convolutional encoder and a Transformer decoder to generate ghost-free HDR images.
no code implementations • 16 Nov 2022 • Yu Yuan, Jiaqi Wu, Lindong Wang, Zhongliang Jing, Henry Leung, Shuyuan Zhu, Han Pan
Capturing highly appreciated star field images is extremely challenging due to light pollution, the requirements of specialized hardware, and the high level of photographic skills needed.
1 code implementation • 18 Oct 2022 • Yu Yuan, Jiaqi Wu, Zhongliang Jing, Henry Leung, Han Pan
In this article, we present a hybrid model consisting of a convolutional encoder and a Transformer-based decoder to fuse multimodal images.
no code implementations • 19 Sep 2022 • Weizhen Ma, Zhongliang Jing, Peng Dong, Henry Leung
The amplitude information of target returns has been incorporated into many tracking algorithms for performance improvements.
no code implementations • 18 Sep 2021 • Jian Hu, Hongya Tuo, Shizhao Zhang, Chao Wang, Haowen Zhong, Zhikang Zou, Zhongliang Jing, Henry Leung, Ruping Zou
Partial Domain adaptation (PDA) aims to solve a more practical cross-domain learning problem that assumes target label space is a subset of source label space.
no code implementations • 26 Jun 2021 • Shizhao Zhang, Hongya Tuo, Jian Hu, Zhongliang Jing
Multi-scale instance level features alignment is presented to reduce instance domain shift effectively , such as variations in object appearance and viewpoint.