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检索条件"任意字段=2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011"
21179 条 记 录,以下是131-140 订阅
排序:
On the Faithfulness of vision Transformer Explanations
On the Faithfulness of Vision Transformer Explanations
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wu, Junyi Kang, Weitai Tang, Hao Hong, Yuan Yan, Yan IIT Dept Comp Sci Chicago IL 60616 USA Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA Univ Connecticut Dept Comp Sci Storrs CT USA
To interpret vision Transformers, post-hoc explanations assign salience scores to input pixels, providing human-understandable heatmaps. However, whether these interpretations reflect true rationales behind the model&... 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
Spectral and Polarization vision: Spectro-polarimetric Real-world Dataset
Spectral and Polarization Vision: Spectro-polarimetric Real-...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Jeon, Yujin Cho, Eunsue Kim, Youngchan Moon, Yunseong Omer, Khalid Heide, Felix Baek, Seung-Hwan POSTECH Pohang South Korea Meta Menlo Pk CA USA Princeton Univ Princeton NJ 08544 USA
Image datasets are essential not only in validating existing methods in computer vision but also in developing new methods. Many image datasets exist, consisting of trichromatic intensity images taken with RGB cameras... 详细信息
来源: 评论
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
Language Model Guided Interpretable Video Action Reasoning
Language Model Guided Interpretable Video Action Reasoning
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wang, Ning Zhu, Guangming Li, H. S. Zhang, Liang Shah, Syed Afaq Ali Bennamoun, Mohammed Xidian Univ Xian Peoples R China Edith Cowan Univ Joondalup Australia Univ Western Australia Perth Australia
While neural networks have excelled in video action recognition tasks, their "black-box" nature often obscures the understanding of their decision-making processes. Recent approaches used inherently interpre... 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
GRAM: Global Reasoning for Multi-Page VQA
GRAM: Global Reasoning for Multi-Page VQA
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Blau, Tsachi Fogel, Sharon Ronen, Roi Goltst, Alona Per, Shahar Tsi Ben Avraham, Elad Aberdam, Aviad Ganz, Roy Litman, Ron Technion Haifa Israel AWS AI Labs Shanghai Peoples R China
The increasing use of transformer-based large language models brings forward the challenge of processing long sequences. In document visual question answering (DocVQA), leading methods focus on the single-page setting... 详细信息
来源: 评论
Building vision-Language Models on Solid Foundations with Masked Distillation
Building Vision-Language Models on Solid Foundations with Ma...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Sameni, Sepehr Kafle, Kushal Tan, Hao Jenni, Simon Univ Bern Bern Switzerland Adobe Res San Jose CA USA
Recent advancements in vision-Language Models (VLMs) have marked a significant leap in bridging the gap between computer vision and natural language processing. However, traditional VLMs, trained through contrastive l... 详细信息
来源: 评论
HybridNeRF: Efficient Neural Rendering via Adaptive Volumetric Surfaces
HybridNeRF: Efficient Neural Rendering via Adaptive Volumetr...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Turki, Haithem Agrawal, Vasu Bulo, Samuel Rota Porzi, Lorenzo Kontschieder, Peter Ramanan, Deva Zollhofer, Michael Richardt, Christian Meta Real Labs Menlo Pk CA 94025 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA
Neural radiance fields provide state-of-the-art view synthesis quality but tend to be slow to render. One reason is that they make use of volume rendering, thus requiring many samples (and model queries) per ray at re... 详细信息
来源: 评论
Improved Visual Grounding through Self-Consistent Explanations
Improved Visual Grounding through Self-Consistent Explanatio...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: He, Ruozhen Cascante-Bonilla, Paola Yang, Ziyan Berg, Alexander C. Ordonez, Vicente Rice Univ Houston TX 77005 USA Univ Calif Irvine Irvine CA USA
vision-and-language models trained to match images with text can be combined with visual explanation methods to point to the locations of specific objects in an image. Our work shows that the localization -"groun... 详细信息
来源: 评论