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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition Workshops"
23095 条 记 录,以下是301-310 订阅
排序:
LQMFormer: Language-aware Query Mask Transformer for Referring Image Segmentation
LQMFormer: Language-aware Query Mask Transformer for Referri...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Shah, Nisarg A. Vibashan, V. S. Patel, Vishal M. Johns Hopkins Univ Baltimore MD 21218 USA
Referring Image Segmentation (RIS) aims to segment objects from an image based on a language description. Recent advancements have introduced transformer-based methods that leverage cross-modal dependencies, significa... 详细信息
来源: 评论
RMT: Retentive Networks Meet vision Transformers
RMT: Retentive Networks Meet Vision Transformers
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Fan, Qihang Huang, Huaibo Chen, Mingrui Liu, Hongmin He, Ran Chinese Acad Sci Inst Automat MAIS & CRIPAC Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Univ Sci & Technol Beijing Beijing Peoples R China
vision Transformer (ViT) has gained increasing attention in the computer vision community in recent years. However, the core component of ViT, Self-Attention, lacks explicit spatial priors and bears a quadratic comput... 详细信息
来源: 评论
PELA: Learning Parameter-Efficient Models with Low-Rank Approximation
PELA: Learning Parameter-Efficient Models with Low-Rank Appr...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Guo, Yangyang Wang, Guangzhi Kankanhalli, Mohan Natl Univ Singapore Singapore Singapore
Applying a pre-trained large model to downstream tasks is prohibitive under resource-constrained conditions. Re-cent dominant approaches for addressing efficiency issues involve adding a few learnable parameters to th... 详细信息
来源: 评论
User-Guided Variable Rate Learned Image Compression
User-Guided Variable Rate Learned Image Compression
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Gupta, Rushil Suryateja, B., V Kapoor, Nikhil Jaiswal, Rajat Nangi, Sharmila Kulkarni, Kuldeep Adobe Res Bengaluru India Indian Inst Technol Delhi Delhi India Stanford Univ Stanford CA 94305 USA
We propose a learning-based image compression method that achieves any arbitrary input bitrate via user-guided bit allocation to preferred regions. We verify our hypothesis of incorporating user guidance for bitrate c... 详细信息
来源: 评论
Synthesize, Diagnose, and Optimize: Towards Fine-Grained vision-Language Understanding
Synthesize, Diagnose, and Optimize: Towards Fine-Grained Vis...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Peng, Wujian Xi, Sicheng You, Zuyao Lan, Shiyi Wu, Zuxuan Fudan Univ Sch CS Shanghai Key Lab Intell Info Proc Shanghai Peoples R China Shanghai Collaborat Innovat Ctr Intelligent Visua Shanghai Peoples R China NVIDIA Shenzhen Guangdong Peoples R China
vision language models (VLM) have demonstrated remarkable performance across various downstream tasks. However, understanding fine-grained visual-linguistic concepts, such as attributes and inter-object relationships,... 详细信息
来源: 评论
ViT-CoMer: vision Transformer with Convolutional Multi-scale Feature Interaction for Dense Predictions
ViT-CoMer: Vision Transformer with Convolutional Multi-scale...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xia, Chunlong Wang, Xinliang Lv, Feng Hao, Xin Shi, Yifeng Baidu Inc Beijing Peoples R China
Although vision Transformer (ViT) has achieved significant success in computer vision, it does not perform well in dense prediction tasks due to the lack of inner-patch information interaction and the limited diversit... 详细信息
来源: 评论
Robustness and Adaptation to Hidden Factors of Variation
Robustness and Adaptation to Hidden Factors of Variation
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Paul, William Burlina, Philippe Johns Hopkins Univ Appl Phys Lab Laurel MD 20723 USA
We tackle here a specific, still not widely addressed aspect, of AI robustness, which consists of seeking invariance / insensitivity of model performance to hidden factors of variations in the data. Towards this end, ... 详细信息
来源: 评论
SMM-Conv: Scalar Matrix Multiplication with Zero Packing for Accelerated Convolution
SMM-Conv: Scalar Matrix Multiplication with Zero Packing for...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Ofir, Amir Ben-Artzi, Gil Ariel Univ Ariel Israel
We present a novel approach for accelerating convolutions during inference for CPU-based architectures. The most common method of computation involves packing the image into the columns of a matrix (im2col) and perfor... 详细信息
来源: 评论
On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?
On the test-time zero-shot generalization of vision-language...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zanella, Maxime Ben Ayed, Ismail UCLouvain Louvain Belgium UMons Mons Belgium ETS Montreal Montreal PQ Canada
The development of large vision-language models, notably CLIP, has catalyzed research into effective adaptation techniques, with a particular focus on soft prompt tuning. Conjointly, test-time augmentation, which util... 详细信息
来源: 评论
Compositional Chain-of-Thought Prompting for Large Multimodal Models
Compositional Chain-of-Thought Prompting for Large Multimoda...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Mitra, Chancharik Huang, Brandon Darrell, Trevor Herzig, Roei Univ Calif Berkeley Berkeley CA 94720 USA
The combination of strong visual backbones and Large Language Model (LLM) reasoning has led to Large Multimodal Models (LMMs) becoming the current standard for a wide range of vision and language (VL) tasks. However, ... 详细信息
来源: 评论