Zobrazeno 1 - 10
of 250
pro vyhledávání: '"Huang, Fuxiang"'
In the real world, where information is abundant and diverse across different modalities, understanding and utilizing various data types to improve retrieval systems is a key focus of research. Multimodal composite retrieval integrates diverse modali
Externí odkaz:
http://arxiv.org/abs/2409.05405
Unsupervised domain adaptation (UDA) intends to transfer knowledge from a labeled source domain to an unlabeled target domain. Many current methods focus on learning feature representations that are both discriminative for classification and invarian
Externí odkaz:
http://arxiv.org/abs/2408.00288
Autor:
He, Yuting, Huang, Fuxiang, Jiang, Xinrui, Nie, Yuxiang, Wang, Minghao, Wang, Jiguang, Chen, Hao
Foundation model, which is pre-trained on broad data and is able to adapt to a wide range of tasks, is advancing healthcare. It promotes the development of healthcare artificial intelligence (AI) models, breaking the contradiction between limited AI
Externí odkaz:
http://arxiv.org/abs/2404.03264
Person re-identification (ReID) has made great strides thanks to the data-driven deep learning techniques. However, the existing benchmark datasets lack diversity, and models trained on these data cannot generalize well to dynamic wild scenarios. To
Externí odkaz:
http://arxiv.org/abs/2403.15119
Mixed-Modal Image Retrieval (MMIR) as a flexible search paradigm has attracted wide attention. However, previous approaches always achieve limited performance, due to two critical factors are seriously overlooked. 1) The contribution of image and tex
Externí odkaz:
http://arxiv.org/abs/2312.06179
Autor:
Huang, Fuxiang, Zhang, Lei
Interactive Image Retrieval (IIR) aims to retrieve images that are generally similar to the reference image but under the requested text modification. The existing methods usually concatenate or sum the features of image and text simply and roughly,
Externí odkaz:
http://arxiv.org/abs/2304.07747
Publikováno v:
In Ocean Engineering 15 November 2024 312 Part 3
Publikováno v:
In Atmospheric Research 15 June 2024 303
Autor:
Fang, Fei, Jin, Ye, Chen, Hongtao, Lin, Huayan, Li, Yuyan, Xiong, Yanbin, Meng, Fancheng, Cao, Liangliang, Huang, Fuxiang, Ma, Li, Wang, Xiao-jun, Ren, Haishen
Publikováno v:
In Journal of Luminescence May 2024 269
Domain adaptive image retrieval includes single-domain retrieval and cross-domain retrieval. Most of the existing image retrieval methods only focus on single-domain retrieval, which assumes that the distributions of retrieval databases and queries a
Externí odkaz:
http://arxiv.org/abs/2003.03293