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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251-260 订阅
排序:
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
Finding Lottery Tickets in vision Models via Data-driven Spectral Foresight Pruning
Finding Lottery Tickets in Vision Models via Data-driven Spe...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Iurada, Leonardo Ciccone, Marco Tommasi, Tatiana Politecn Torino Turin Italy
Recent advances in neural network pruning have shown how it is possible to reduce the computational costs and memory demands of deep learning models before training. We focus on this framework and propose a new prunin... 详细信息
来源: 评论
Situational Awareness Matters in 3D vision Language Reasoning
Situational Awareness Matters in 3D Vision Language Reasonin...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Man, Yunze Gui, Liang-Yan Wang, Yu-Xiong Univ Illinois Urbana IL 61801 USA
Being able to carry out complicated vision language reasoning tasks in 3D space represents a significant milestone in developing household robots and human-centered embodied AI. In this work, we demonstrate that a cri... 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
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
ZeroShape: Regression-based Zero-shot Shape Reconstruction
ZeroShape: Regression-based Zero-shot Shape Reconstruction
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Huang, Zixuan Stojanov, Stefan Thai, Anh Jampani, Varun Rehg, James M. Univ Illinois Champaign IL 61820 USA Georgia Inst Technol Atlanta GA 30332 USA Stabil AI London England
We study the problem of single-image zero-shot 3D shape reconstruction. Recent works learn zero-shot shape reconstruction through generative modeling of 3D assets, but these models are computationally expensive at tra... 详细信息
来源: 评论
Differentiable Display Photometric Stereo
Differentiable Display Photometric Stereo
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Choi, Seokjun Yoon, Seungwoo Nam, Giljoo Lee, Seungyong Baek, Seung-Hwan POSTECH Pohang South Korea Meta Real Labs Menlo Pk CA USA
Photometric stereo leverages variations in illumination conditions to reconstruct surface normals. Display photometric stereo, which employs a conventional monitor as an illumination source, has the potential to overc... 详细信息
来源: 评论
Fooling Polarization-based vision using Locally Controllable Polarizing Projection
Fooling Polarization-based Vision using Locally Controllable...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Zhuoxiao Zhong, Zhihang Nobuhara, Shohei Nishino, Ko Zheng, Yinqiang Univ Tokyo Tokyo Japan Shanghai Artificial Intelligence Lab Shanghai Peoples R China Kyoto Univ Kyoto Japan
Polarization is a fundamental property of light that encodes abundant information regarding surface shape, material, illumination and viewing geometry. The computer vision community has witnessed a blossom of polariza...
来源: 评论
Test-Time Adaptation for Depth Completion
Test-Time Adaptation for Depth Completion
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Park, Hyoungseob Gupta, Anjali Wong, Alex Yale Vision Lab New Haven CT 06501 USA
It is common to observe performance degradation when transferring models trained on some (source) datasets to target testing data due to a domain gap between them. Existing methods for bridging this gap, such as domai... 详细信息
来源: 评论
Part-aware Unified Representation of Language and Skeleton for Zero-shot Action recognition
Part-aware Unified Representation of Language and Skeleton f...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhu, Anqi Ke, Qiuhong Gong, Mingming Bailey, James Univ Melbourne Melbourne Vic Australia Monash Univ Parkville Vic 3052 Australia Wellington Rd Clayton Vic 3800 Australia
While remarkable progress has been made on supervised skeleton-based action recognition, the challenge of zero-shot recognition remains relatively unexplored. In this paper, we argue that relying solely on aligning la... 详细信息
来源: 评论