Zobrazeno 1 - 10
of 567
pro vyhledávání: '"Hu, Xiaobin"'
Autor:
Ji, Xiaozhong, Lin, Chuming, Ding, Zhonggan, Tai, Ying, Zhu, Junwei, Hu, Xiaobin, Luo, Donghao, Ge, Yanhao, 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:
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:
Tai, Hanchen, He, Qingdong, Zhang, Jiangning, Qian, Yijie, Zhang, Zhenyu, Hu, Xiaobin, Wang, Yabiao, Liu, Yong
Open-vocabulary 3D scene understanding presents a significant challenge in the field. Recent advancements have sought to transfer knowledge embedded in vision language models from the 2D domain to 3D domain. However, these approaches often require le
Externí odkaz:
http://arxiv.org/abs/2405.15580
Autor:
Li, Hongwei Bran, Navarro, Fernando, Ezhov, Ivan, Bayat, Amirhossein, Das, Dhritiman, Kofler, Florian, Shit, Suprosanna, Waldmannstetter, Diana, Paetzold, Johannes C., Hu, Xiaobin, Wiestler, Benedikt, Zimmer, Lucas, Amiranashvili, Tamaz, Prabhakar, Chinmay, Berger, Christoph, Weidner, Jonas, Alonso-Basant, Michelle, Rashid, Arif, Baid, Ujjwal, Adel, Wesam, Ali, Deniz, Baheti, Bhakti, Bai, Yingbin, Bhatt, Ishaan, Cetindag, Sabri Can, Chen, Wenting, Cheng, Li, Dutand, Prasad, Dular, Lara, Elattar, Mustafa A., Feng, Ming, Gao, Shengbo, Huisman, Henkjan, Hu, Weifeng, Innani, Shubham, Jiat, Wei, Karimi, Davood, Kuijf, Hugo J., Kwak, Jin Tae, Le, Hoang Long, Lia, Xiang, Lin, Huiyan, Liu, Tongliang, Ma, Jun, Ma, Kai, Ma, Ting, Oksuz, Ilkay, Holland, Robbie, Oliveira, Arlindo L., Pal, Jimut Bahan, Pei, Xuan, Qiao, Maoying, Saha, Anindo, Selvan, Raghavendra, Shen, Linlin, Silva, Joao Lourenco, Spiclin, Ziga, Talbar, Sanjay, Wang, Dadong, Wang, Wei, Wang, Xiong, Wang, Yin, Xia, Ruiling, Xu, Kele, Yan, Yanwu, Yergin, Mert, Yu, Shuang, Zeng, Lingxi, Zhang, YingLin, Zhao, Jiachen, Zheng, Yefeng, Zukovec, Martin, Do, Richard, Becker, Anton, Simpson, Amber, Konukoglu, Ender, Jakab, Andras, Bakas, Spyridon, Joskowicz, Leo, Menze, Bjoern
Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a significant challenge in achieving consistent and reliable image segmentat
Externí odkaz:
http://arxiv.org/abs/2405.18435
Autor:
He, Liren, Jiang, Zhengkai, Peng, Jinlong, Liu, Liang, Du, Qiangang, Hu, Xiaobin, Zhu, Wenbing, Chi, Mingmin, Wang, Yabiao, Wang, Chengjie
In the field of multi-class anomaly detection, reconstruction-based methods derived from single-class anomaly detection face the well-known challenge of "learning shortcuts", wherein the model fails to learn the patterns of normal samples as it shoul
Externí odkaz:
http://arxiv.org/abs/2403.11561
Autor:
Huang, Siyuan, Ponomarenko, Iaroslav, Jiang, Zhengkai, Li, Xiaoqi, Hu, Xiaobin, Gao, Peng, Li, Hongsheng, Dong, Hao
The integration of Multimodal Large Language Models (MLLMs) with robotic systems has significantly enhanced the ability of robots to interpret and act upon natural language instructions. Despite these advancements, conventional MLLMs are typically tr
Externí odkaz:
http://arxiv.org/abs/2403.11289
Autor:
He, Qingdong, Peng, Jinlong, Jiang, Zhengkai, Hu, Xiaobin, Zhang, Jiangning, Nie, Qiang, Wang, Yabiao, Wang, Chengjie
Recent success of vision foundation models have shown promising performance for the 2D perception tasks. However, it is difficult to train a 3D foundation network directly due to the limited dataset and it remains under explored whether existing foun
Externí odkaz:
http://arxiv.org/abs/2403.06403
Autor:
Hu, Xiaobin, Peng, Xu, Luo, Donghao, Ji, Xiaozhong, Peng, Jinlong, Jiang, Zhengkai, Zhang, Jiangning, Jin, Taisong, Wang, Chengjie, Ji, Rongrong
Due to the difficulty and labor-consuming nature of getting highly accurate or matting annotations, there only exists a limited amount of highly accurate labels available to the public. To tackle this challenge, we propose a DiffuMatting which inheri
Externí odkaz:
http://arxiv.org/abs/2403.06168
Autor:
Wang, Sen, Zhang, Jiangning, Cao, Weijian, Hu, Xiaobin, Li, Moran, Ji, Xiaozhong, Tan, Xin, Li, Mengtian, Xie, Zhifeng, Wang, Chengjie, Ma, Lizhuang
The body movements accompanying speech aid speakers in expressing their ideas. Co-speech motion generation is one of the important approaches for synthesizing realistic avatars. Due to the intricate correspondence between speech and motion, generatin
Externí odkaz:
http://arxiv.org/abs/2403.02905
Autor:
Tang, Peng, Yan, Xintong, Nan, Yang, Hu, Xiaobin, Krammer, Bjoern H Menzee. Sebastian, Lasser, Tobias
Most convolutional neural network (CNN) based methods for skin cancer classification obtain their results using only dermatological images. Although good classification results have been shown, more accurate results can be achieved by considering the
Externí odkaz:
http://arxiv.org/abs/2312.04189