Zobrazeno 1 - 10
of 141
pro vyhledávání: '"Wang, Chengjie"'
Autor:
Li, Bang, Luo, Donghao, Liang, Yujie, Yang, Jing, Ding, Zengmao, Peng, Xu, Jiang, Boyuan, Han, Shengwei, Sui, Dan, Qin, Peichao, Wu, Pian, Wang, Chaoyang, Qi, Yun, Jin, Taisong, Wang, Chengjie, Huang, Xiaoming, Shu, Zhan, Ji, Rongrong, Liu, Yongge, Wu, Yunsheng
Oracle bone inscriptions(OBI) is the earliest developed writing system in China, bearing invaluable written exemplifications of early Shang history and paleography. However, the task of deciphering OBI, in the current climate of the scholarship, can
Externí odkaz:
http://arxiv.org/abs/2407.03900
Anomaly detection, the technique of identifying abnormal samples using only normal samples, has attracted widespread interest in industry. Existing one-model-per-category methods often struggle with limited generalization capabilities due to their fo
Externí odkaz:
http://arxiv.org/abs/2407.01905
Autor:
Ji, Xiaozhong, Lin, Chuming, Ding, Zhonggan, Tai, Ying, Yang, Jian, Zhu, Junwei, Hu, Xiaobin, Zhang, Jiangning, Luo, Donghao, Wang, Chengjie
Person-generic audio-driven face generation is a challenging task in computer vision. Previous methods have achieved remarkable progress in audio-visual synchronization, but there is still a significant gap between current results and practical appli
Externí odkaz:
http://arxiv.org/abs/2406.18284
Autor:
Yan, Zhiyuan, Yao, Taiping, Chen, Shen, Zhao, Yandan, Fu, Xinghe, Zhu, Junwei, Luo, Donghao, Yuan, Li, Wang, Chengjie, Ding, Shouhong, Wu, Yunsheng
We propose a new comprehensive benchmark to revolutionize the current deepfake detection field to the next generation. Predominantly, existing works identify top-notch detection algorithms and models by adhering to the common practice: training detec
Externí odkaz:
http://arxiv.org/abs/2406.13495
Autor:
Kong, Lingjie, Wu, Kai, Hu, Xiaobin, Han, Wenhui, Peng, Jinlong, Xu, Chengming, Luo, Donghao, Zhang, Jiangning, Wang, Chengjie, Fu, Yanwei
Text-to-image based object customization, aiming to generate images with the same identity (ID) as objects of interest in accordance with text prompts and reference images, has made significant progress. However, recent customizing research is domina
Externí odkaz:
http://arxiv.org/abs/2406.11643
Autor:
Zhang, Jiangning, He, Haoyang, Gan, Zhenye, He, Qingdong, Cai, Yuxuan, Xue, Zhucun, Wang, Yabiao, Wang, Chengjie, Xie, Lei, Liu, Yong
Visual anomaly detection aims to identify anomalous regions in images through unsupervised learning paradigms, with increasing application demand and value in fields such as industrial inspection and medical lesion detection. Despite significant prog
Externí odkaz:
http://arxiv.org/abs/2406.03262
Autor:
Nie, Qiang, Fu, Weifu, Lin, Yuhuan, Li, Jialin, Zhou, Yifeng, Liu, Yong, Zhu, Lei, Wang, Chengjie
Instance-incremental learning (IIL) focuses on learning continually with data of the same classes. Compared to class-incremental learning (CIL), the IIL is seldom explored because IIL suffers less from catastrophic forgetting (CF). However, besides r
Externí odkaz:
http://arxiv.org/abs/2406.03065
Autor:
Wang, Chengjie, Zhu, Haokun, Peng, Jinlong, Wang, Yue, Yi, Ran, Wu, Yunsheng, Ma, Lizhuang, Zhang, Jiangning
Existing industrial anomaly detection methods primarily concentrate on unsupervised learning with pristine RGB images. Yet, both RGB and 3D data are crucial for anomaly detection, and the datasets are seldom completely clean in practical scenarios. T
Externí odkaz:
http://arxiv.org/abs/2406.02263
Autor:
Wu, Kai, Jiang, Boyuan, Jiang, Zhengkai, He, Qingdong, Luo, Donghao, Wang, Shengzhi, Liu, Qingwen, Wang, Chengjie
Multimodal large language models (MLLMs) contribute a powerful mechanism to understanding visual information building on large language models. However, MLLMs are notorious for suffering from hallucinations, especially when generating lengthy, detail
Externí odkaz:
http://arxiv.org/abs/2405.20081
Autor:
Wang, Qilin, Jiang, Zhengkai, Xu, Chengming, Zhang, Jiangning, Wang, Yabiao, Zhang, Xinyi, Cao, Yun, Cao, Weijian, Wang, Chengjie, Fu, Yanwei
Human image animation involves generating a video from a static image by following a specified pose sequence. Current approaches typically adopt a multi-stage pipeline that separately learns appearance and motion, which often leads to appearance degr
Externí odkaz:
http://arxiv.org/abs/2405.18156