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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000"
19489 条 记 录,以下是4731-4740 订阅
排序:
StyleCineGAN: Landscape Cinemagraph Generation Using a Pre-trained StyleGAN
StyleCineGAN: Landscape Cinemagraph Generation Using a Pre-t...
收藏 引用
conference on computer vision and pattern recognition (cvpr)
作者: Jongwoo Choi Kwanggyoon Seo Amirsaman Ashtari Junyong Noh Visual Media Lab KAIST
We propose a method that can generate cinemagraphs automatically from a still landscape image using a pre-trained StyleGAN. Inspired by the success of recent un-conditional video generation, we leverage a powerful pre... 详细信息
来源: 评论
Promptable Behaviors: Personalizing Multi-Objective Rewards from Human Preferences
Promptable Behaviors: Personalizing Multi-Objective Rewards ...
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conference on computer vision and pattern recognition (cvpr)
作者: Minyoung Hwang Luca Weihs Chanwoo Park Kimin Lee Aniruddha Kembhavi Kiana Ehsani PRIOR @ Allen Institute for AI Massachusetts Institute of Technology Korea Advanced Institute of Science and Technology
Customizing robotic behaviors to be aligned with di-verse human preferences is an underexplored challenge in the field of embodied AI. In this paper, we present Prompt-able Behaviors, a novel framework that facilitate... 详细信息
来源: 评论
Uncertainty-Aware Camera Pose Estimation from Points and Lines
Uncertainty-Aware Camera Pose Estimation from Points and Lin...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Vakhitov, Alexander Ferraz Colomina, Luis Agudo, Antonio Moreno-Noguer, Francesc SLAMCore Ltd London England Kognia Sports Intelligence Barcelona Spain CSIC UPC Inst Robot & Informat Ind Barcelona Spain
Perspective-n-Point-and-Line (PnPL) algorithms aim at fast, accurate, and robust camera localization with respect to a 3D model from 2D-3D feature correspondences, being a major part of modern robotic and AR/VR system... 详细信息
来源: 评论
ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search
ViPNAS: Efficient Video Pose Estimation via Neural Architect...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Xu, Lumin Guan, Yingda Jin, Sheng Liu, Wentao Qian, Chen Luo, Ping Ouyang, Wanli Wang, Xiaogang Chinese Univ Hong Kong Hong Kong Peoples R China SenseTime Res Beijing Peoples R China Univ Hong Kong Hong Kong Peoples R China Tetras AI Beijing Peoples R China Univ Sydney Camperdown NSW Australia
Human pose estimation has achieved significant progress in recent years. However, most of the recent methods focus on improving accuracy using complicated models and ignoring real-time efficiency. To achieve a better ... 详细信息
来源: 评论
Improved Image Matting via Real-time User Clicks and Uncertainty Estimation
Improved Image Matting via Real-time User Clicks and Uncerta...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wei, Tianyi Chen, Dongdong Zhou, Wenbo Liao, Jing Zhao, Hanqing Zhang, Weiming Yu, Nenghai Univ Sci & Technol China Hefei Anhui Peoples R China Microsoft Cloud AI Hefei Peoples R China City Univ Hong Kong Hong Kong Peoples R China
Image matting is a fundamental and challenging problem in computer vision and graphics. Most existing matting methods leverage a user-supplied trimap as an auxiliary input to produce good alpha matte. However, obtaini... 详细信息
来源: 评论
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion
Robust Instance Segmentation through Reasoning about Multi-O...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Yuan, Xiaoding Kortylewski, Adam Sun, Yihong Yuille, Alan Tongji Univ Shanghai Peoples R China Johns Hopkins Univ Baltimore MD 21218 USA
Analyzing complex scenes with Deep Neural Networks is a challenging task, particularly when images contain multiple objects that partially occlude each other. Existing approaches to image analysis mostly process objec... 详细信息
来源: 评论
Connecting vision and Language with Video Localized Narratives
Connecting Vision and Language with Video Localized Narrativ...
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conference on computer vision and pattern recognition (cvpr)
作者: Paul Voigtlaender Soravit Changpinyo Jordi Pont-Tuset Radu Soricut Vittorio Ferrari Google Research
We propose Video Localized Narratives, a new form of multimodal video annotations connecting vision and language. In the original Localized Narratives [36], annotators speak and move their mouse simultaneously on an i...
来源: 评论
Atom-Level Optical Chemical Structure recognition with Limited Supervision
Atom-Level Optical Chemical Structure Recognition with Limit...
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conference on computer vision and pattern recognition (cvpr)
作者: Martijn Oldenhof Edward De Brouwer Adam Arany Yves Moreau ESAT - STADIUS KU Leuven Belgium Yale University USA
Identifying the chemical structure from a graphical representation, or image, of a molecule is a challenging pattern recognition task that would greatly benefit drug development. Yet, existing methods for chemical str... 详细信息
来源: 评论
Refine Myself by Teaching Myself : Feature Refinement via Self-Knowledge Distillation
Refine Myself by Teaching Myself : Feature Refinement via Se...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Ji, Mingi Shin, Seungjae Hwang, Seunghyun Park, Gibeom Moon, Il-Chul Korea Adv Inst Sci & Technol KAIST Daejeon South Korea Looko Inc Los Angeles CA USA Summary AI Seoul South Korea
Knowledge distillation is a method of transferring the knowledge from a pretrained complex teacher model to a student model, so a smaller network can replace a large teacher network at the deployment stage. To reduce ... 详细信息
来源: 评论
Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation
Retrieval-Augmented Layout Transformer for Content-Aware Lay...
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conference on computer vision and pattern recognition (cvpr)
作者: Daichi Horita Naoto Inoue Kotaro Kikuchi Kota Yamaguchi Kiyoharu Aizawa The University of Tokyo CyberAgent
Content-aware graphic layout generation aims to automatically arrange visual elements along with a given content, such as an e-commerce product image. In this paper, we argue that the current layout generation approac... 详细信息
来源: 评论