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检索条件"任意字段=1994 IEEE Computer-Society Conference on Computer Vision and Pattern Recognition"
22906 条 记 录,以下是4651-4660 订阅
排序:
LLM-Seg: Bridging Image Segmentation and Large Language Model Reasoning
LLM-Seg: Bridging Image Segmentation and Large Language Mode...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Junchi Wang Lei Ke ETH Zurich
Understanding human instructions to identify the target objects is vital for perception systems. In recent years, the advancements of Large Language Models (LLMs) have introduced new possibilities for image segmentati... 详细信息
来源: 评论
AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries
AdCo: Adversarial Contrast for Efficient Learning of Unsuper...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Hu, Qianjiang Wang, Xiao Hu, Wei Qi, Guo-Jun Peking Univ Beijing Peoples R China Purdue Univ W Lafayette IN 47907 USA Lab MAchine Percept & LEarning MAPLE Beijing Peoples R China
Contrastive learning relies on constructing a collection of negative examples that are sufficiently hard to discriminate against positive queries when their representations are self-trained. Existing contrastive learn... 详细信息
来源: 评论
Learning by Watching
Learning by Watching
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Jimuyang Ohn-Bar, Eshed Boston Univ Boston MA 02215 USA
When in a new situation or geographical location, human drivers have an extraordinary ability to watch others and learn maneuvers that they themselves may have never performed. In contrast, existing techniques for lea... 详细信息
来源: 评论
Classifier Guided Cluster Density Reduction for Dataset Selection
Classifier Guided Cluster Density Reduction for Dataset Sele...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Cheng Chang Keyu Long Zijian Li Himanshu Rai Layer 6 AI
In this paper, we address the challenge of selecting an optimal dataset from a source pool with annotations to enhance performance on a target dataset derived from a different source. This is important in scenarios wh... 详细信息
来源: 评论
Adapting the Segment Anything Model During Usage in Novel Situations
Adapting the Segment Anything Model During Usage in Novel Si...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Robin Schön Julian Lorenz Katja Ludwig Rainer Lienhart Universität Augsburg Augsburg
The interactive segmentation task consists in the creation of object segmentation masks based on user interactions. The most common way to guide a model towards producing a correct segmentation consists in clicks on t... 详细信息
来源: 评论
Learning by Aligning Videos in Time
Learning by Aligning Videos in Time
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Haresh, Sanjay Kumar, Sateesh Coskun, Huseyin Syed, Shahram N. Konin, Andrey Zia, M. Zeeshan Quoc-Huy Tran Retrocausal Inc Seattle WA 98052 USA
We present a self-supervised approach for learning video representations using temporal video alignment as a pretext task, while exploiting both frame-level and video-level information. We leverage a novel combination... 详细信息
来源: 评论
Dynamic Addition of Noise in a Diffusion Model for Anomaly Detection
Dynamic Addition of Noise in a Diffusion Model for Anomaly D...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Justin Tebbe Jawad Tayyub Otto von Guericke University Magdeburg Magdeburg Germany Endress + Hauser Maulburg Germany
Diffusion models have found valuable applications in anomaly detection by capturing the nominal data distribution and identifying anomalies via reconstruction. Despite their merits, they struggle to localize anomalies... 详细信息
来源: 评论
Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
Cross-Domain Gradient Discrepancy Minimization for Unsupervi...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Du, Zhekai Li, Jingjing Su, Hongzu Zhu, Lei Lu, Ke Univ Elect Sci & Technol China Chengdu Sichuan Peoples R China Shandong Normal Univ Jinan Shandong Peoples R China
Unsupervised Domain Adaptation (UDA) aims to generalize the knowledge learned from a well-labeled source domain to an unlabled target domain. Recently, adversarial domain adaptation with two distinct classifiers (bi-c... 详细信息
来源: 评论
DaFF: Dual Attentive Feature Fusion for Multispectral Pedestrian Detection
DaFF: Dual Attentive Feature Fusion for Multispectral Pedest...
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ieee computer society conference on computer vision and pattern recognition Workshops (CVPRW)
作者: Afnan Althoupety Li-Yun Wang Wu-Chi Feng Banafsheh Rekabdar Portland State University USA
Inspired by how humans perceive and interpret the world using multiple senses, multi-modal learning involves integrating information from multiple modalities to improve understanding and performance in various tasks. ... 详细信息
来源: 评论
Delving Deep into Many-to-many Attention for Few-shot Video Object Segmentation
Delving Deep into Many-to-many Attention for Few-shot Video ...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chen, Haoxin Wu, Hanjie Zhao, Nanxuan Ren, Sucheng He, Shengfeng South China Univ Technol Sch Comp Sci & Engn Guangzhou Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China
This paper tackles the task of Few-Shot Video Object Segmentation (FSVOS), i.e., segmenting objects in the query videos with certain class specified in a few labeled support images. The key is to model the relationshi... 详细信息
来源: 评论