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检索条件"任意字段=2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022"
11141 条 记 录,以下是4911-4920 订阅
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LiBRe: A Practical Bayesian Approach to Adversarial Detection
LiBRe: A Practical Bayesian Approach to Adversarial Detectio...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Deng, Zhijie Yang, Xiao Xu, Shizhen Su, Hang Zhu, Jun Tsinghua Univ Dept Comp Sci & Tech BNRist Ctr Inst AITsinghua Bosch Joint ML CtrTHBI Lab Beijing 100084 Peoples R China RealAI Beijing Peoples R China
Despite their appealing flexibility, deep neural networks (DNNs) are vulnerable against adversarial examples. Various adversarial defense strategies have been proposed to resolve this problem, but they typically demon... 详细信息
来源: 评论
DSC-PoseNet: Learning 6DoF Object Pose Estimation via Dual-scale Consistency
DSC-PoseNet: Learning 6DoF Object Pose Estimation via Dual-s...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Yang, Zongxin Yu, Xin Yang, Yi Baidu Res Beijing Peoples R China Univ Technol Sydney ReLER Sydney NSW Australia
Compared to 2D object bounding-box labeling, it is very difficult for humans to annotate 3D object poses, especially when depth images of scenes are unavailable. This paper investigates whether we can estimate the obj... 详细信息
来源: 评论
Look Before You Leap: Learning Landmark Features for One-Stage Visual Grounding
Look Before You Leap: Learning Landmark Features for One-Sta...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Huang, Binbin Lian, Dongze Luo, Weixin Gao, Shenghua ShanghaiTech Univ Shanghai Peoples R China Shanghai Engn Res Ctr Intelligent Vis & Imaging Shanghai Peoples R China
An LBYL ('Look Before You Leap') Network is proposed for end-to-end trainable one-stage visual grounding. The idea behind LBYL-Net is intuitive and straightforward: we follow a language's description to lo... 详细信息
来源: 评论
Improving Image recognition by Retrieving from Web-Scale Image-Text Data
Improving Image Recognition by Retrieving from Web-Scale Ima...
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conference on computer vision and pattern recognition (cvpr)
作者: Ahmet Iscen Alireza Fathi Cordelia Schmid Google Research
Retrieval augmented models are becoming increasingly popular for computer vision tasks after their recent success in NLP problems. The goal is to enhance the recognition capabilities of the model by retrieving similar...
来源: 评论
Farewell to Mutual Information: Variational Distillation for Cross-Modal Person Re-Identification
Farewell to Mutual Information: Variational Distillation for...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Tian, Xudong Zhang, Zhizhong Lin, Shaohui Qu, Yanyun Xie, Yuan Ma, Lizhuang East China Normal Univ Shanghai Peoples R China Xiamen Univ Xiamen Peoples R China Shanghai Jiao Tong Univ Shanghai Peoples R China
The Information Bottleneck (IB) provides an information theoretic principle for representation learning, by retaining all information relevant for predicting label while minimizing the redundancy. Though IB principle ... 详细信息
来源: 评论
Interventional Video Grounding with Dual Contrastive Learning
Interventional Video Grounding with Dual Contrastive Learnin...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Nan, Guoshun Qiao, Rui Xiao, Yao Liu, Jun Leng, Sicong Zhang, Hao Lu, Wei Singapore Univ Technol & Design StatNLP Res Grp Singapore Singapore Shanghai Jiao Tong Univ Shanghai Peoples R China Singapore Univ Technol & Design Informat Syst Technol & Design Singapore Singapore Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore ASTAR Inst High Performance Comp Singapore Singapore
Video grounding aims to localize a moment from an untrimmed video for a given textual query. Existing approaches focus more on the alignment of visual and language stimuli with various likelihood-based matching or reg... 详细信息
来源: 评论
Recognizing Rigid patterns of Unlabeled Point Clouds by Complete and Continuous Isometry Invariants with no False Negatives and no False Positives
Recognizing Rigid Patterns of Unlabeled Point Clouds by Comp...
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conference on computer vision and pattern recognition (cvpr)
作者: Daniel Widdowson Vitaliy Kurlin Computer Science department University of Liverpool UK
Rigid structures such as cars or any other solid objects are often represented by finite clouds of unlabeled points. The most natural equivalence on these point clouds is rigid motion or isometry maintaining all inter...
来源: 评论
Not just Compete, but Collaborate: Local Image-to-Image Translation via Cooperative Mask Prediction
Not just Compete, but Collaborate: Local Image-to-Image Tran...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Kim, Daejin Khan, Mohammad Azam Choo, Jaegul Korea Adv Inst Sci & Technol Daejeon South Korea Dhaka Power Distribut Co Ltd Dhaka Bangladesh
Facial attribute editing aims to manipulate the image with the desired attribute while preserving the other details. Recently, generative adversarial networks along with the encoder-decoder architecture have been util... 详细信息
来源: 评论
How and What to Learn: Taxonomizing Self-Supervised Learning for 3D Action recognition  22
How and What to Learn: Taxonomizing Self-Supervised Learning...
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22nd ieee/cvf Winter conference on Applications of computer vision (WACV)
作者: Ben Tanfous, Amor Zerroug, Aimen Linsley, Drew Serre, Thomas Toulouse Univ Artificial & Nat Intelligence Toulouse Inst Toulouse France Brown Univ Carney Inst Brain Sci Dept Cognit Linguist Psychol Sci Providence RI 02912 USA
There are two competing standards for self-supervised learning in action recognition from 3D skeletons. Su et al., 2020 [31] used an auto-encoder architecture and an image reconstruction objective function to achieve ... 详细信息
来源: 评论
Prototype Augmentation and Self-Supervision for Incremental Learning
Prototype Augmentation and Self-Supervision for Incremental ...
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ieee/cvf conference on computer vision and pattern recognition (cvpr)
作者: Zhu, Fei Zhang, Xu-Yao Wang, Chuang Yin, Fei Liu, Cheng-Lin Chinese Acad Sci Inst Automat NLPR Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing 100190 Peoples R China
Despite the impressive performance in many individual tasks, deep neural networks suffer from catastrophic forgetting when learning new tasks incrementally. Recently, various incremental learning methods have been pro... 详细信息
来源: 评论