Zobrazeno 1 - 10
of 9 565
pro vyhledávání: '"TANG, Ming"'
Autor:
Magli, Giulio
Publikováno v:
Archaeological Research in Asia Volume 17, March 2019, Pages 98-108
The royal Chinese mausoleums of the Tang, Ming and Qing Chinese dynasties are astounding ensables of monuments, conceived and built to assure to the Emperors immortality in the afterlife and perennial fame on earth. To this aim, a series of cognitive
Externí odkaz:
http://arxiv.org/abs/1804.00264
Autor:
He, Jinghan, Zhu, Kuan, Guo, Haiyun, Fang, Junfeng, Hua, Zhenglin, Jia, Yuheng, Tang, Ming, Chua, Tat-Seng, Wang, Jinqiao
Large vision-language models (LVLMs) have made substantial progress in integrating large language models (LLMs) with visual inputs, enabling advanced multimodal reasoning. Despite their success, a persistent challenge is hallucination-where generated
Externí odkaz:
http://arxiv.org/abs/2412.13949
Visual Anomaly Detection (VAD) aims to identify abnormal samples in images that deviate from normal patterns, covering multiple domains, including industrial, logical, and medical fields. Due to the domain gaps between these fields, existing VAD meth
Externí odkaz:
http://arxiv.org/abs/2412.03342
Overfitting has long been stigmatized as detrimental to model performance, especially in the context of anomaly detection. Our work challenges this conventional view by introducing a paradigm shift, recasting overfitting as a controllable and strateg
Externí odkaz:
http://arxiv.org/abs/2412.00560
Continual learning (CL) is crucial for language models to dynamically adapt to the evolving real-world demands. To mitigate the catastrophic forgetting problem in CL, data replay has been proven a simple and effective strategy, and the subsequent dat
Externí odkaz:
http://arxiv.org/abs/2411.06171
Large Multimodal Models (LMMs) have achieved significant breakthroughs in various vision-language and vision-centric tasks based on auto-regressive modeling. However, these models typically focus on either vision-centric tasks, such as visual groundi
Externí odkaz:
http://arxiv.org/abs/2410.16163
Autor:
Kou, Wei-Bin, Lin, Qingfeng, Tang, Ming, Ye, Rongguang, Wang, Shuai, Zhu, Guangxu, Wu, Yik-Chung
Street Scene Semantic Understanding (denoted as TriSU) is a complex task for autonomous driving (AD). However, inference model trained from data in a particular geographical region faces poor generalization when applied in other regions due to inter-
Externí odkaz:
http://arxiv.org/abs/2409.19560
In the realm of emerging real-time networked applications like cyber-physical systems (CPS), the Age of Information (AoI) has merged as a pivotal metric for evaluating the timeliness. To meet the high computational demands, such as those in intellige
Externí odkaz:
http://arxiv.org/abs/2409.16832