Zobrazeno 1 - 10
of 623
pro vyhledávání: '"Wang, Chengjie"'
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
Autor:
Zhang, Sihe, He, Qingdong, Peng, Jinlong, Li, Yuxi, Jiang, Zhengkai, Wu, Jiafu, Chi, Mingmin, Wang, Yabiao, Wang, Chengjie
Image retrieval aims to identify visually similar images within a database using a given query image. Traditional methods typically employ both global and local features extracted from images for matching, and may also apply re-ranking techniques to
Externí odkaz:
http://arxiv.org/abs/2405.17718
Transformers have revolutionized the point cloud learning task, but the quadratic complexity hinders its extension to long sequence and makes a burden on limited computational resources. The recent advent of RWKV, a fresh breed of deep sequence model
Externí odkaz:
http://arxiv.org/abs/2405.15214