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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition"
23240 条 记 录,以下是171-180 订阅
排序:
Split to Merge: Unifying Separated Modalities for Unsupervised Domain Adaptation
Split to Merge: Unifying Separated Modalities for Unsupervis...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Li, Xinyao Li, Yuke Du, Zhekai Li, Fengling Lu, Ke Li, Jingjing Univ Elect Sci & Technol China Chengdu Peoples R China Boston Coll Chestnut Hill MA 02167 USA Univ Technol Sydney Sydney NSW Australia
Large vision-language models (VLMs) like CLIP have demonstrated good zero-shot learning performance in the unsupervised domain adaptation task. Yet, most transfer approaches for VLMs focus on either the language or vi... 详细信息
来源: 评论
One Embedding to Predict Them All: Visible and Thermal Universal Face Representations for Soft Biometric Estimation via vision Transformers
One Embedding to Predict Them All: Visible and Thermal Unive...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Mirabet-Herranz, Nelida Galdi, Chiara Dugelay, Jean-Luc EURECOM Campus SophiaTech450 Route Chappes F-06410 Biot France
Human faces encode a vast amount of information including not only uniquely distinctive features of the individual but also demographic information such as a person's age, gender, and weight. Such information is r... 详细信息
来源: 评论
Summarize the Past to Predict the Future: Natural Language Descriptions of Context Boost Multimodal Object Interaction Anticipation
Summarize the Past to Predict the Future: Natural Language D...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Pasca, Razvan-George Gavryushin, Alexey Hamza, Muhammad Kuo, Yen-Ling Mo, Kaichun Van Gool, Luc Hilliges, Otmar Wang, Xi Swiss Fed Inst Technol Zurich Switzerland Univ Zurich Zurich Switzerland Univ Virginia Charlottesville VA USA NVIDIA Santa Clara CA USA Katholieke Univ Leuven Leuven Belgium INSAIT Sofia Bulgaria
We study object interaction anticipation in egocentric videos. This task requires an understanding of the spatio-temporal context formed by past actions on objects, coined action context. We propose TransFusion, a mul... 详细信息
来源: 评论
Task-aligned Part-aware Panoptic Segmentation through Joint Object-Part Representations
Task-aligned Part-aware Panoptic Segmentation through Joint ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: de Geus, Daan Dubbelman, Gijs Eindhoven Univ Technol Eindhoven Netherlands
Part-aware panoptic segmentation (PPS) requires (a) that each foreground object and background region in an image is segmented and classified, and (b) that all parts within foreground objects are segmented, classified... 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
Convolutional Prompting meets Language Models for Continual Learning
Convolutional Prompting meets Language Models for Continual ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Roy, Anurag Moulick, Riddhiman Verma, Vinay K. Ghosh, Saptarshi Das, Abir IIT Kharagpur Kharagpur W Bengal India IML Amazon India Hyderabad India
Continual Learning (CL) enables machine learning models to learn from continuously shifting new training data in absence of data from old tasks. Recently, pretrained vision transformers combined with prompt tuning hav... 详细信息
来源: 评论
AM-RADIO: Agglomerative vision Foundation Model Reduce All Domains Into One
AM-RADIO: Agglomerative Vision Foundation Model Reduce All D...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Ranzinger, Mike Heinrich, Greg Kautz, Jan Molchanov, Pavlo NVIDIA Santa Clara CA 95051 USA
A handful of visual foundation models (VFMs) have recently emerged as the backbones for numerous downstream tasks. VFMs like CLIP, DINOv2, SAM are trained with distinct objectives, exhibiting unique characteristics fo... 详细信息
来源: 评论
Transductive Zero-Shot and Few-Shot CLIP
Transductive Zero-Shot and Few-Shot CLIP
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Martin, Segolene Huang, Yunshi Shakeri, Fereshteh Pesquet, Jean-Christophe Ben Ayed, Ismail Univ Paris Saclay CVN Cent Supelec INRIA Paris France ETS Montreal Montreal PQ Canada
Transductive inference has been widely investigated in few-shot image classification, but completely overlooked in the recent, fast growing literature on adapting vision-langage models like CLIP. This paper addresses ... 详细信息
来源: 评论
Fair-VPT: Fair Visual Prompt Tuning for Image Classification
Fair-VPT: Fair Visual Prompt Tuning for Image Classification
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Park, Sungho Byun, Hy Eran Yonsei Univ Seoul South Korea
Despite the remarkable success of vision Transformers (ViT) across diverse fields in computer vision, they have a clear drawback of expensive adaption cost for downstream tasks due to the increased scale. To address t... 详细信息
来源: 评论
H-ViT: A Hierarchical vision Transformer for Deformable Image Registration
H-ViT: A Hierarchical Vision Transformer for Deformable Imag...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Ghahremani, Morteza Khateri, Mohammad Jian, Bailiang Wiestler, Benedikt Adeli, Ehsan Wachinger, Christian Tech Univ Munich Munich Germany Munich Ctr Machine Learning Munich Germany Univ Eastern Finland Espoo Finland Stanford Univ Stanford CA 94305 USA
This paper introduces a novel top-down representation approach for deformable image registration, which estimates the deformation field by capturing various short-and long-range flow features at different scale levels... 详细信息
来源: 评论