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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4641-4650 订阅
排序:
Text-Driven Image Editing via Learnable Regions
Text-Driven Image Editing via Learnable Regions
收藏 引用
conference on computer vision and pattern recognition (cvpr)
作者: Yuanze Lin Yi-Wen Chen Yi-Hsuan Tsai Lu Jiang Ming-Hsuan Yang University of Oxford UC Merced Google
Language has emerged as a natural interface for image editing. In this paper, we introduce a method for region- based image editing driven by textual prompts, without the need for user-provided masks or sketches. Spec... 详细信息
来源: 评论
Probabilistic Model Distillation for Semantic Correspondence
Probabilistic Model Distillation for Semantic Correspondence
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Li, Xin Fan, Deng-Ping Yang, Fan Luo, Ao Cheng, Hong Liu, Zicheng Grp 42 G42 Abu Dhabi U Arab Emirates Inception Inst AI Abu Dhabi U Arab Emirates Megvii Technol Beijing Peoples R China UESTC Chengdu Peoples R China Microsoft Redmond WA USA
Semantic correspondence is a fundamental problem in computer vision, which aims at establishing dense correspondences across images depicting different instances under the same category. This task is challenging due t... 详细信息
来源: 评论
Text-Guided Explorable Image Super-Resolution
Text-Guided Explorable Image Super-Resolution
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conference on computer vision and pattern recognition (cvpr)
作者: Kanchana Vaishnavi Gandikota Paramanand Chandramouli Institute for Vision and Graphics University of Siegen
In this paper, we introduce the problem of zero-shot text-guided exploration of the solutions to open-domain image super-resolution. Our goal is to allow users to explore diverse, semantically accurate reconstructions... 详细信息
来源: 评论
Pre-Trained Image Processing Transformer
Pre-Trained Image Processing Transformer
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Chen, Hanting Wang, Yunhe Guo, Tianyu Xu, Chang Deng, Yiping Liu, Zhenhua Ma, Siwei Xu, Chunjing Xu, Chao Gao, Wen Peking Univ Dept Machine Intelligence Key Lab Machine Percept MOE Beijing Peoples R China Huawei Technol Noahs Ark Lab Shenzhen Peoples R China Univ Sydney Fac Engn Sch Comp Sci Sydney NSW Australia Huawei Technol Cent Software Inst Shenzhen Peoples R China Peking Univ Sch Elect Engn & Comp Sci Inst Digital Media Beijing Peoples R China Peng Cheng Lab Shenzhen Peoples R China
As the computing power of modern hardware is increasing strongly, pre-trained deep learning models (e.g., BERT, GPT-3) learned on large-scale datasets have shown their effectiveness over conventional methods. The big ... 详细信息
来源: 评论
Learning to Predict Activity Progress by Self-Supervised Video Alignment
Learning to Predict Activity Progress by Self-Supervised Vid...
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conference on computer vision and pattern recognition (cvpr)
作者: Gerard Donahue Ehsan Elhamifar Northeastern University Northeastern University Boston MA USA
In this paper, we tackle the problem of self-supervised video alignment and activity progress prediction using in-the-wild videos. Our proposed self-supervised representation learning method carefully addresses differ... 详细信息
来源: 评论
Feedback control of event cameras
Feedback control of event cameras
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Delbruck, Tobi Graca, Rui Paluch, Marcin UZH ETH Zurich Inst Neuroinformat Zurich Switzerland
Dynamic vision sensor event cameras produce a variable data rate stream of brightness change events. Event production at the pixel level is controlled by threshold, bandwidth, and refractory period bias current parame... 详细信息
来源: 评论
Visual recognition by Request
Visual Recognition by Request
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conference on computer vision and pattern recognition (cvpr)
作者: Chufeng Tang Lingxi Xie Xiaopeng Zhang Xiaolin Hu Qi Tian Department of Computer Science and Technology Tsinghua University Huawei Inc. Chinese Institute for Brain Research (CIBR) IDG/McGovern Institute for Brain Research THBI Tsinghua University
Humans have the ability of recognizing visual semantics in an unlimited granularity, but existing visual recognition algorithms cannot achieve this goal. In this paper, we establish a new paradigm named visual recogni...
来源: 评论
ReDet: A Rotation-equivariant Detector for Aerial Object Detection
ReDet: A Rotation-equivariant Detector for Aerial Object Det...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Han, Jiaming Ding, Jian Xue, Nan Xia, Gui-Song Wuhan Univ Wuhan Peoples R China
Recently, object detection in aerial images has gained much attention in computer vision. Different from objects in natural images, aerial objects are often distributed with arbitrary orientation. Therefore, the detec... 详细信息
来源: 评论
Track, Check, Repeat: An EM Approach to Unsupervised Tracking
Track, Check, Repeat: An EM Approach to Unsupervised Trackin...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Harley, Adam W. Zuo, Yiming Wen, Jing Mangal, Ayush Potdar, Shubhankar Chaudhry, Ritwick Fragkiadaki, Katerina Carnegie Mellon Univ Pittsburgh PA 15213 USA
We propose an unsupervised method for detecting and tracking moving objects in 3D, in unlabelled RGB-D videos. The method begins with classic handcrafted techniques for segmenting objects using motion cues: we estimat... 详细信息
来源: 评论
S2R-DepthNet: Learning a Generalizable Depth-specific Structural Representation
S2R-DepthNet: Learning a Generalizable Depth-specific Struct...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Chen, Xiaotian Wang, Yuwang Chen, Xuejin Zeng, Wenjun Univ Sci & Technol China Hefei Peoples R China Microsoft Res Asia Beijing Peoples R China
Human can infer the 3D geometry of a scene from a sketch instead of a realistic image, which indicates that the spatial structure plays a fundamental role in understanding the depth of scenes. We are the first to expl... 详细信息
来源: 评论