Zobrazeno 1 - 10
of 166
pro vyhledávání: '"Du, Penghui"'
This paper introduces Multi-Garment Customized Model Generation, a unified framework based on Latent Diffusion Models (LDMs) aimed at addressing the unexplored task of synthesizing images with free combinations of multiple pieces of clothing. The met
Externí odkaz:
http://arxiv.org/abs/2408.05206
Autor:
Du, Penghui, Wang, Yu, Sun, Yifan, Wang, Luting, Liao, Yue, Zhang, Gang, Ding, Errui, Wang, Yan, Wang, Jingdong, Liu, Si
Existing methods enhance open-vocabulary object detection by leveraging the robust open-vocabulary recognition capabilities of Vision-Language Models (VLMs), such as CLIP.However, two main challenges emerge:(1) A deficiency in concept representation,
Externí odkaz:
http://arxiv.org/abs/2407.11335
Autor:
Qu, Youzhi, Wei, Chen, Du, Penghui, Che, Wenxin, Zhang, Chi, Ouyang, Wanli, Bian, Yatao, Xu, Feiyang, Hu, Bin, Du, Kai, Wu, Haiyan, Liu, Jia, Liu, Quanying
During the evolution of large models, performance evaluation is necessarily performed to assess their capabilities and ensure safety before practical application. However, current model evaluations mainly rely on specific tasks and datasets, lacking
Externí odkaz:
http://arxiv.org/abs/2402.02547
Autor:
Song, Zhiyun, Du, Penghui, Yan, Junpeng, Li, Kailu, Shou, Jianzhong, Lai, Maode, Fan, Yubo, Xu, Yan
Self-supervised pretraining attempts to enhance model performance by obtaining effective features from unlabeled data, and has demonstrated its effectiveness in the field of histopathology images. Despite its success, few works concentrate on the ext
Externí odkaz:
http://arxiv.org/abs/2309.07394
Autor:
Wang, Luting, Liu, Yi, Du, Penghui, Ding, Zihan, Liao, Yue, Qi, Qiaosong, Chen, Biaolong, Liu, Si
Open-vocabulary object detection aims to provide object detectors trained on a fixed set of object categories with the generalizability to detect objects described by arbitrary text queries. Previous methods adopt knowledge distillation to extract kn
Externí odkaz:
http://arxiv.org/abs/2303.05892
Transfer learning improves the performance of the target task by leveraging the data of a specific source task: the closer the relationship between the source and the target tasks, the greater the performance improvement by transfer learning. In neur
Externí odkaz:
http://arxiv.org/abs/2206.03950
Autor:
Qu, Youzhi, Du, Penghui, Che, Wenxin, Wei, Chen, Zhang, Chi, Ouyang, Wanli, Bian, Yatao, Xu, Feiyang, Hu, Bin, Du, Kai, Wu, Haiyan, Liu, Jia, Liu, Quanying
Publikováno v:
In The Innovation 4 March 2024 5(2)
Autor:
Dai, Qin, Yu, Guangfei, Qi, Juanjuan, Wang, Yanan, Xing, Lei, Wang, Yihao, Zhang, Zhijie, Zhong, Xiaolin, Fang, Zhimo, Du, Penghui, Lyu, Lai, Wang, Lidong
Publikováno v:
In Applied Catalysis B: Environment and Energy January 2024 340
Publikováno v:
In Ecotoxicology and Environmental Safety 15 October 2023 265
Autor:
Yin, Gege, Zhang, Peng, Wang, Yinghui, Aftab, Bilal, Du, Penghui, Zhang, Qiang, Chen, Guoping, Wang, Mengke, Yang, Biwei, Wang, Senhao, Mo, Jiangming, Zhang, Wei, Wang, Junjian
Publikováno v:
In Geochimica et Cosmochimica Acta 1 October 2023 358:162-173