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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition Workshops"
23198 条 记 录,以下是331-340 订阅
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Simulated Quantization, Real Power Savings
Simulated Quantization, Real Power Savings
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: van Baalen, Mart Kahne, Brian Mahurin, Eric Kuzmin, Andrey Skliar, Andrii Nagel, Markus Blankevoort, Tijmen Qualcomm AI Res San Diego CA 92121 USA
Reduced precision hardware-based matrix multiplication accelerators are commonly employed to reduce power consumption of neural network inference. Multiplier designs used in such accelerators possess an interesting pr... 详细信息
来源: 评论
Towards CNN map representation and compression for camera relocalisation  31
Towards CNN map representation and compression for camera re...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Contreras, Luis Mayol-Cuevas, Walterio Univ Bristol Dept Comp Sci Bristol Avon England
This paper presents a study on the use of Convolutional Neural Networks for camera relocalisation and its application to map compression. We follow state of the art visual relocalisation results and evaluate the respo... 详细信息
来源: 评论
Automatic Play Segmentation of Hockey Videos
Automatic Play Segmentation of Hockey Videos
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Pidaparthy, Hemanth Dowling, Michael H. Elder, James H. York Univ N York ON Canada Queens Univ Kingston ON Canada
Most team sports such as hockey involve periods of active play interleaved with breaks in play. When watching a game remotely, many fans would prefer an abbreviated game showing only periods of active play. Here we ad... 详细信息
来源: 评论
Private-Shared Disentangled Multimodal VAE for Learning of Latent Representations
Private-Shared Disentangled Multimodal VAE for Learning of L...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Lee, Mihee Pavlovic, Vladimir Rutgers State Univ Piscataway NJ 08854 USA
Multi-modal generative models represent an important family of deep models, whose goal is to facilitate representation learning on data with multiple views or modalities. However, current deep multi-modal models focus... 详细信息
来源: 评论
Residual Feature Pyramid Network for Enhancement of Vascular patterns
Residual Feature Pyramid Network for Enhancement of Vascular...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Kotwal, Ketan Marcel, Sebastien Idiap Res Inst Martigny Switzerland Univ Lausanne Lausanne Switzerland
The accuracy of finger vein recognition systems gets degraded due to low and uneven contrast between veins and surroundings, often resulting in poor detection of vein patterns. We propose a finger-vein enhancement tec... 详细信息
来源: 评论
Dealing with Missing Modalities in the Visual Question Answer-Difference Prediction Task through Knowledge Distillation
Dealing with Missing Modalities in the Visual Question Answe...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cho, Jae Won Kim, Dong-Jin Choi, Jinsoo Jung, Yunjae Kweon, In So Korea Adv Inst Sci & Technol Daejeon South Korea
In this work, we address the issues of the missing modalities that have arisen from the Visual Question Answer-Difference prediction task and find a novel method to solve the task at hand. We address the missing modal... 详细信息
来源: 评论
MVFuseNet: Improving End-to-End Object Detection and Motion Forecasting through Multi-View Fusion of LiDAR Data
MVFuseNet: Improving End-to-End Object Detection and Motion ...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Laddha, Ankit Gautam, Shivam Palombo, Stefan Pandey, Shreyash Vallespi-Gonzalez, Carlos Aurora Innovat Mountain View CA 94043 USA
In this work, we propose MVFuseNet, a novel end-to-end method for joint object detection and motion forecasting from a temporal sequence of LiDAR data. Most existing methods operate in a single view by projecting data... 详细信息
来源: 评论
Generative Flows as a General Purpose Solution for Inverse Problems
Generative Flows as a General Purpose Solution for Inverse P...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chavez, Jose A. San Pablo Catholic Univ Arequipa Peru
Due to the success of generative flows to model data distributions, they have been explored in inverse problems. Given a pre-trained generative flow, previous work proposed to minimize the 2-norm of the latent variabl... 详细信息
来源: 评论
Shot in the Dark: Few-Shot Learning with No Base-Class Labels
Shot in the Dark: Few-Shot Learning with No Base-Class Label...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chen, Zitian Maji, Subhransu Learned-Miller, Erik Univ Massachusetts Amherst Amherst MA 01003 USA
Few-shot learning aims to build classifiers for new classes from a small number of labeled examples and is commonly facilitated by access to examples from a distinct set of 'base classes'. The difference in da... 详细信息
来源: 评论
AnimalFormer: Multimodal vision Framework for Behavior-based Precision Livestock Farming
AnimalFormer: Multimodal Vision Framework for Behavior-based...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Qazi, Ahmed Razzaq, Taha Iqbal, Asim Tibbling Technol Redmond WA 98052 USA
We introduce a multimodal vision framework for precision livestock farming, harnessing the power of GroundingDINO, HQSAM, and ViTPose models. This integrated suite enables comprehensive behavioral analytics from video... 详细信息
来源: 评论