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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops"
12859 条 记 录,以下是121-130 订阅
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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
Rotated Rectangles for Symbolized Building Footprint Extraction  31
Rotated Rectangles for Symbolized Building Footprint Extract...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Dickenson, Matt Gueguen, Lionel UBER Technol Inc San Francisco CA 94103 USA
Building footprints (BFP) provide useful visual context for users of digital maps when navigating in space. This paper proposes a method for extracting and symbolizing building footprints from satellite imagery using ... 详细信息
来源: 评论
Reconsidering CO2 emissions from computer vision
Reconsidering CO2 emissions from Computer Vision
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Fu, Andre Hosseini, Mahdi S. Plataniotis, Konstantinos N. Univ Toronto Toronto ON Canada Univ New Brunswick Fredericton NB Canada
Climate change is a pressing issue that is currently affecting and will affect every part of our lives. It's becoming incredibly vital we, as a society, address the climate crisis as a universal effort, including ... 详细信息
来源: 评论
Land Cover Classification from Satellite Imagery With U-Net and Lovasz-Softmax Loss  31
Land Cover Classification from Satellite Imagery With U-Net ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Rakhlin, Alexander Davydow, Alex Nikolenko, Sergey Neuromat OU EE-10111 Tallinn Estonia
The land cover classification task of the DeepGlohe Challenge presents significant obstacles even to state of the art segmentation models due to a small amount of data, incomplete and sometimes incorrect labeling, and... 详细信息
来源: 评论
Area Under the ROC Curve Maximization for Metric Learning
Area Under the ROC Curve Maximization for Metric Learning
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Gajic, Bojana Amato, Ariel Baldrich, Ramon van de Weijer, Joost Gatta, Carlo Vintra Inc Barcelona Spain Comp Vis Ctr Barcelona Spain
Most popular metric learning losses have no direct relation with the evaluation metrics that are subsequently applied to evaluate their performance. We hypothesize that training a metric learning model by maximizing t... 详细信息
来源: 评论
Sketch-QNet: A Quadruplet ConvNet for Color Sketch-based Image Retrieval
Sketch-QNet: A Quadruplet ConvNet for Color Sketch-based Ima...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Fuentes, Anibal Saavedra, Jose M. Impresee Inc 600 Calif St San Francisco CA 94108 USA
Architectures based on siamese networks with triplet loss have shown outstanding performance on the image-based similarity search problem. This approach attempts to discriminate between positive (relevant) and negativ... 详细信息
来源: 评论
Filter Distribution Templates in Convolutional Networks for Image Classification Tasks
Filter Distribution Templates in Convolutional Networks for ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Izquierdo-Cordova, Ramon Mayol-Cuevas, Walterio Univ Bristol Dept Comp Sci Bristol Avon England
Neural network designers have reached progressive accuracy by increasing models depth, introducing new layer types and discovering new combinations of layers. A common element in many architectures is the distribution... 详细信息
来源: 评论
Conjugate Adder Net (CAddNet) - a Space-Efficient Approximate CNN
Conjugate Adder Net (CAddNet) - a Space-Efficient Approximat...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Shen, Lulan Ziaeefard, Maryam Meyer, Brett Gross, Warren Clark, James J. McGill Univ Montreal PQ Canada
The AdderNet was recently developed as a way to implement deep neural networks without needing multiplication operations to combine weights and inputs. Instead, absolute values of the difference between weights and in... 详细信息
来源: 评论
SuperLoRA: Parameter-Efficient Unified Adaptation for Large vision Models
SuperLoRA: Parameter-Efficient Unified Adaptation for Large ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Chen, Xiangyu Liu, Jing Wang, Ye Wang, Pu (Perry) Brand, Matthew Wang, Guanghui Koike-Akino, Toshiaki Univ Kansas Lawrence KS 66045 USA Mitsubishi Elect Res Labs MERL Cambridge MA 02139 USA Toronto Metropolitan Univ Toronto ON M5B 2K3 Canada
Low-rank adaptation (LoRA) and its variants are widely employed in fine-tuning large models, including large language models for natural language processing and diffusion models for computer vision. This paper propose... 详细信息
来源: 评论
RDONet: Rate-Distortion Optimized Learned Image Compression with Variable Depth
RDONet: Rate-Distortion Optimized Learned Image Compression ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Brand, Fabian Fischer, Kristian Kopte, Alexander Windsheimer, Marc Kaup, Andre Friedrich Alexander Univ Erlangen Nurnberg Multimedia Commun & Signal Proc Cauerstr 7 D-91058 Erlangen Germany
Rate-distortion optimization (RDO) is responsible for large gains in image and video compression. While RDO is a standard tool in traditional image and video coding, it is not yet widely used in novel end-to-end train... 详细信息
来源: 评论