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检索条件"任意字段=2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013"
4491 条 记 录,以下是61-70 订阅
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AIGeN: An Adversarial Approach for Instruction Generation in VLN
AIGeN: An Adversarial Approach for Instruction Generation in...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Rawal, Niyati Bigazzi, Roberto Baraldi, Lorenzo Cucchiara, Rita Univ Modena & Reggio Emilia Modena Italy
In the last few years, the research interest in vision-and-Language Navigation (VLN) has grown significantly. VLN is a challenging task that involves an agent following human instructions and navigating in a previousl... 详细信息
来源: 评论
Potential Risk Localization via Weak Labeling out of Blind Spot
Potential Risk Localization via Weak Labeling out of Blind S...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Shimomura, Kota Hirakawa, Tsubasa Yamashita, Takayoshi Fujiyoshi, Hironobu Chubu Univ Kasugai Aichi Japan
Achieving fully autonomous driving requires not only understanding the current surrounding conditions but also predicting how objects that could lead to potential risks may change in the future. Predicting potential r... 详细信息
来源: 评论
Interpreting COVID Lateral Flow Tests' Results with Foundation Models
Interpreting COVID Lateral Flow Tests' Results with Foundati...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Pandey, Stuti Myers-Dean, Josh Reynolds, Jarek Gurari, Danna Univ Colorado Boulder CO 80309 USA Univ Texas Austin Austin TX 78712 USA
Lateral flow tests (LFTs) enable rapid, low-cost testing for health conditions including Covid, pregnancy, HIV, and malaria. Automated readers of LFT results can yield many benefits including empowering blind people t... 详细信息
来源: 评论
Exploring the Zero-Shot Capabilities of vision-Language Models for Improving Gaze Following
Exploring the Zero-Shot Capabilities of Vision-Language Mode...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Gupta, Anshul Vuillecard, Pierre Farkhondeh, Arya Odobez, Jean-Marc Idiap Res Inst Martigny Switzerland Ecole Polytech Fed Lausanne Lausanne Switzerland
Contextual cues related to a person's pose and interactions with objects and other people in the scene can provide valuable information for gaze following. While existing methods have focused on dedicated cue extr... 详细信息
来源: 评论
ELSA: Exploiting Layer-wise N:M Sparsity for vision Transformer Acceleration
ELSA: Exploiting Layer-wise N:M Sparsity for Vision Transfor...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Huang, Ning-Chi Chang, Chi-Chih Lin, Wei-Cheng Taka, Endri Marculescu, Diana Wu, Kai-Chiang Natl Yang Ming Chiao Tung Univ Hsinchu Taiwan Univ Texas Austin Austin TX USA
N:M sparsity is an emerging model compression method supported by more and more accelerators to speed up sparse matrix multiplication in deep neural networks. Most existing N:M sparsity methods compress neural network... 详细信息
来源: 评论
QAttn: Efficient GPU Kernels for mixed-precision vision Transformers
QAttn: Efficient GPU Kernels for mixed-precision Vision Tran...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Kluska, Piotr Castello, Adrian Scheidegger, Florian Malossi, A. Cristiano I. Quintana-Orti, Enrique S. IBM Res Europe Ruschlikon Switzerland Univ Politecn Valencia Valencia Spain
vision Transformers have demonstrated outstanding performance in computer vision tasks. Nevertheless, this superior performance for large models comes at the expense of increasing memory usage for storing the paramete... 详细信息
来源: 评论
CAGE: Circumplex Affect Guided Expression Inference
CAGE: Circumplex Affect Guided Expression Inference
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Wagner, Niklas Maetzler, Felix Vossberg, Samed R. Schneider, Helen Pavlitska, Svetlana Zoellner, J. Marius Karlsruhe Inst Technol KIT Karlsruhe Germany FZI Res Ctr Informat Technol Karlsruhe Germany
Understanding emotions and expressions is a task of interest across multiple disciplines, especially for improving user experiences. Contrary to the common perception, it has been shown that emotions are not discrete ... 详细信息
来源: 评论
Knowledge Distillation for Efficient Instance Semantic Segmentation with Transformers
Knowledge Distillation for Efficient Instance Semantic Segme...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Maohui Halstead, Michael McCool, Chris Univ Bonn Bonn Germany Lamarr Inst Machine Learning & Artificial Intelli Dortmund Germany
Instance-based semantic segmentation provides detailed per-pixel scene understanding information crucial for both computer vision and robotics applications. However, state-of-the-art approaches such as Mask2Former are... 详细信息
来源: 评论
Exploring the Benefits of vision Foundation Models for Unsupervised Domain Adaptation
Exploring the Benefits of Vision Foundation Models for Unsup...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Englert, Bruno B. Piva, Fabrizio J. Kerssies, Tommie de Geus, Daan Dubbelman, Gijs Eindhoven Univ Technol Eindhoven Netherlands
Achieving robust generalization across diverse data domains remains a significant challenge in computer vision. This challenge is important in safety-critical applications, where deep-neural-network-based systems must... 详细信息
来源: 评论
Segment Anything Model for Road Network Graph Extraction
Segment Anything Model for Road Network Graph Extraction
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Hetang, Congrui Xue, Haoru Le, Cindy Yue, Tianwei Wang, Wenping He, Yihui Carnegie Mellon Univ Pittsburgh PA 15213 USA Columbia Univ New York NY USA
We propose SAM-Road, an adaptation of the Segment Anything Model (SAM) [27] for extracting large-scale, vectorized road network graphs from satellite imagery. To predict graph geometry, we formulate it as a dense sema... 详细信息
来源: 评论