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检索条件"机构=Baidu Research and National Engineering Laboratory for Deep Learning Technology and Application"
100 条 记 录,以下是51-60 订阅
排序:
3D Part Guided Image Editing for Fine-Grained Object Understanding
3D Part Guided Image Editing for Fine-Grained Object Underst...
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Conference on Computer Vision and Pattern Recognition (CVPR)
作者: Zongdai Liu Feixiang Lu Peng Wang Hui Miao Liangjun Zhang Ruigang Yang Bin Zhou State Key Laboratory of Virtual Reality Technology and Systems Beihang University Robotics and Autonomous Driving Laboratory Baidu Research National Engineering Laboratory of Deep Learning Technology and Application China ByteDance Research University of Kentucky Peng Cheng Laboratory Shenzhen China
Holistically understanding an object with its 3D movable parts is essential for visual models of a robot to interact with the world. For example, only by understanding many possible part dynamics of other vehicles (e.... 详细信息
来源: 评论
GBCNs: Genetic Binary Convolutional Networks for enhancing the performance of 1-bit DCNNs
arXiv
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arXiv 2019年
作者: Liu, Chunlei W., Ding Y., Hu B., Zhang J., Liu G., Guo School of Electronic and Information Engineering Beihang University Unmanned System Research Institute Beihang University School of Automation Science and Electrical Engineering Beihang University Shenzhen Institutes of Advanced Technology University of Chinese Academy of Sciences Institute of Deep Learning Baidu Research National Engineering Laboratory for Deep Learning Technology and Application
Training 1-bit deep convolutional neural networks (DCNNs) is one of the most challenging problems in computer vision, because it is much easier to get trapped into local minima than conventional DCNNs. The reason lies... 详细信息
来源: 评论
FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofing
arXiv
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arXiv 2023年
作者: Liu, Ajian Tan, Zichang Yu, Zitong Zhao, Chenxu Wan, Jun Liang, Yanyan Lei, Zhen Zhang, Du Li, Stan Z. Guo, Guodong Beijing China The Institute of Deep Learning Baidu Research National Engineering Laboratory for Deep Learning Technology and Application China The Great Bay University Dongguan523000 China The Mininglamp Academy of Sciences Mininglamp Technology China The Macau University of Science and Technology China The Westlake University China
The availability of handy multi-modal (i.e., RGB-D) sensors has brought about a surge of face anti-spoofing research. However, the current multi-modal face presentation attack detection (PAD) has two defects: (1) The ... 详细信息
来源: 评论
Vision Transformer with Attentive Pooling for Robust Facial Expression Recognition
arXiv
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arXiv 2022年
作者: Xue, Fanglei Wang, Qiangchang Tan, Zichang Ma, Zhongsong Guo, Guodong University of Chinese Academy of Sciences The Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China West Virginia University Morgantown United States Institute of Deep Learning Baidu Research National Engineering Laboratory for Deep Learning Technology and Application Beijing China
Facial Expression Recognition (FER) in the wild is an extremely challenging task. Recently, some Vision Transformers (ViT) have been explored for FER, but most of them perform inferiorly compared to Convolutional Neur... 详细信息
来源: 评论
IoU loss for 2D/3D object detection
arXiv
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arXiv 2019年
作者: Zhou, Dingfu Fang, Jin Song, Xibin Guan, Chenye Yin, Junbo Dai, Yuchao Yang, Ruigang Baidu Research National Engineering Laboratory of Deep Learning Technology and Application China Beijing Lab of Intelligent Information Technology School of Computer Science Beijing Institute of Technology China Northwestern Polytechnical University Xi'an China
In 2D/3D object detection task, Intersection-over-Union (IoU) has been widely employed as an evaluation metric to evaluate the performance of different detectors in the testing stage. However, during the training stag... 详细信息
来源: 评论
RBCN: Rectified Binary convolutional networks for enhancing the Performance of 1-bit DCNNs
arXiv
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arXiv 2019年
作者: Liu, Chunlei Ding, Wenrui Xia, Xin Hu, Yuan Zhang, Baochang Liu, Jianzhuang Zhuang, Bohan Guo, Guodong School of Electronic and Information Engineering Beihang University Unmanned System Research Institute Beihang University School of Automation Science and Electrical Engineering Beihang University Huawei Noah's Ark Lab University of Adelaide Institute of Deep Learning Baidu Research National Engineering Laboratory for Deep Learning Technology and Application
Binarized convolutional neural networks (BCNNs) are widely used to improve memory and computation efficiency of deep convolutional neural networks (DCNNs) for mobile and AI chips based applications. However, current B... 详细信息
来源: 评论
iffDetector: Inference-aware feature filtering for object detection
arXiv
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arXiv 2020年
作者: Mao, Mingyuan Tian, Yuxin Zhang, Baochang Ye, Qixiang Liu, Wanquan Guo, Guodong Doermann, David Beihang University Beijing China University of Chinese Academy of Sciences Beijing China Curtin University Perth Australia Institute of Deep Learning Baidu Research Beijing China National Engineering Laboratory for Deep Learning Technology and Application University at Buffalo Buffalo United States
Modern CNN-based object detectors focus on feature configuration during training but often ignore feature optimization during inference. In this paper, we propose a new feature optimization approach to enhance feature... 详细信息
来源: 评论
FaceScape: A large-scale high quality 3D face dataset and detailed riggable 3D face prediction
arXiv
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arXiv 2020年
作者: Yang, Haotian Zhu, Hao Wang, Yanru Huang, Mingkai Shen, Qiu Yang, Ruigang Cao, Xun Nanjing University China Baidu Research University of Kentucky United States Inceptio Inc National Engineering Laboratory for Deep Learning Technology and Applications China
In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a novel algorithm that is able to predict elaborate riggable 3D face models from a single image input. FaceScape dataset provide... 详细信息
来源: 评论
Out-of-town recommendation with travel intention modeling
arXiv
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arXiv 2021年
作者: Xin, Haoran Lu, Xinjiang Xu, Tong Liu, Hao Gu, Jingjing Dou, Dejing Xiong, Hui University of Science and Technology of China China Business Intelligence Lab Baidu Research China National Engineering Laboratory of Deep Learning Technology and Application China Nanjing University of Aeronautics and Astronautics China Rutgers University United States
Out-of-town recommendation is designed for those users who leave their home-town areas and visit the areas they have never been to before. It is challenging to recommend Point-of-Interests (POIs) for out-of-town users... 详细信息
来源: 评论
Spatial object recommendation with hints: When spatial granularity matters
arXiv
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arXiv 2021年
作者: Luo, Hui Zhou, Jingbo Bao, Zhifeng Li, Shuangli Culpepper, J. Shane Ying, Haochao Liu, Hao Xiong, Hui RMIT University Australia Business Intelligence Lab Baidu Research National Engineering Laboratory of Deep Learning Technology and Application China University of Science and Technology of China China Zhejiang University China Rutgers University United States
Existing spatial object recommendation algorithms generally treat objects identically when ranking them. However, spatial objects often cover different levels of spatial granularity and thereby are heterogeneous. For ... 详细信息
来源: 评论