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检索条件"任意字段=2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016"
20979 条 记 录,以下是331-340 订阅
排序:
SPIN: Simultaneous Perception, Interaction and Navigation
SPIN: Simultaneous Perception, Interaction and Navigation
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Uppal, Shagun Agarwal, Ananye Xiong, Haoyu Shaw, Kenneth Pathak, Deepak Carnegie Mellon Univ Pittsburgh PA 15213 USA
While there has been remarkable progress recently in the fields of manipulation and locomotion, mobile manipulation remains a long-standing challenge. Compared to locomotion or static manipulation, a mobile system mus... 详细信息
来源: 评论
Volumetric Environment Representation for vision-Language Navigation
Volumetric Environment Representation for Vision-Language Na...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Liu, Rui Wang, Wenguan Yan, Yi Zhejiang Univ CCAI ReLER Hangzhou Zhejiang Peoples R China
vision-language navigation (VLN) requires an agent to navigate through an 3D environment based on visual observations and natural language instructions. It is clear that the pivotal factor for successful navigation li... 详细信息
来源: 评论
PEM: Prototype-based Efficient MaskFormer for Image Segmentation
PEM: Prototype-based Efficient MaskFormer for Image Segmenta...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Cavagnero, Niccolo Rosi, Gabriele Cuttano, Claudia Pistilli, Francesca Ciccone, Marco Averta, Giuseppe Cermelli, Fabio Politecn Torino Turin Italy Focoos AI Rome Italy
Recent transformer-based architectures have shown impressive results in the field of image segmentation. Thanks to their flexibility, they obtain outstanding performance in multiple segmentation tasks, such as semanti... 详细信息
来源: 评论
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image recognition
UniRepLKNet: A Universal Perception Large-Kernel ConvNet for...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Ding, Xiaohan Zhang, Yiyuan Ge, Yixiao Zhao, Sijie Song, Lin Yue, Xiangyu Shan, Ying Tencent AI Lab Shenzhen Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China
Large-kernel convolutional neural networks (ConvNets) have recently received extensive research attention, but two unresolved and critical issues demand further investigation. 1) The architectures of existing large-ke... 详细信息
来源: 评论
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimo...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Tong, Shengbang Liu, Zhuang Zhai, Yuexiang Ma, Yi Lecun, Yann Xie, Saining NYU New York NY 10003 USA Meta FAIR Menlo Pk CA 94025 USA Univ Calif Berkeley Berkeley CA USA
Is vision good enough for language? Recent advancements in multimodal models primarily stem from the powerful reasoning abilities of large language models (LLMs). However, the visual component typically depends only o... 详细信息
来源: 评论
Jack of All Tasks, Master of Many: Designing General-purpose Coarse-to-Fine vision-Language Model
Jack of All Tasks, Master of Many: Designing General-purpose...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Pramanick, Shraman Han, Guangxing Hou, Rui Nag, Sayan Lim, Ser-Nam Ballas, Nicolas Wang, Qifan Chellappa, Rama Almahairi, Amjad Johns Hopkins Univ Baltimore MD 21218 USA Meta New York NY 10003 USA Univ Toronto Toronto ON Canada Univ Cent Florida Orlando FL 32816 USA
The ability of large language models (LLMs) to process visual inputs has given rise to general-purpose vision systems, unifying various vision-language (VL) tasks by instruction tuning. However, due to the enormous di...
来源: 评论
Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf vision-Language Models
Emergent Open-Vocabulary Semantic Segmentation from Off-the-...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Luo, Jiayun Khandelwal, Siddhesh Sigal, Leonid Li, Boyang Nanyang Technol Univ Singapore Singapore Univ British Columbia Vector Inst AI Vancouver BC Canada
From image-text pairs, large-scale vision-language models (VLMs) learn to implicitly associate image regions with words, which prove effective for tasks like visual question answering. However, leveraging the learned ... 详细信息
来源: 评论
MULTIFLOW: Shifting Towards Task-Agnostic vision-Language Pruning
MULTIFLOW: Shifting Towards Task-Agnostic Vision-Language Pr...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Farina, Matteo Mancini, Massimiliano Cunegatti, Elia Liu, Gaowen Iacca, Giovanni Ricci, Elisa Univ Trento Trento Italy Cisco Res Res Triangle Pk NC USA Fdn Bruno Kessler Povo Italy
While excellent in transfer learning, vision-Language models (VLMs) come with high computational costs due to their large number of parameters. To address this issue, removing parameters via model pruning is a viable ... 详细信息
来源: 评论
RegionPLC: Regional Point-Language Contrastive Learning for Open-World 3D Scene Understanding
RegionPLC: Regional Point-Language Contrastive Learning for ...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Yang, Jihan Ding, Runyu Deng, Weipeng Wang, Zhe Qi, Xiaojuan Univ Hong Kong Hong Kong Peoples R China SenseTime Res Hong Kong Peoples R China
We propose a lightweight and scalable Regional Point-Language Contrastive learning framework, namely RegionPLC, for open-world 3D scene understanding, aiming to identify and recognize open-set objects and categories. ... 详细信息
来源: 评论
Unravelling Robustness of Deep Face recognition Networks Against Illicit Drug Abuse Images
Unravelling Robustness of Deep Face Recognition Networks Aga...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Dhake, Hruturaj Agarwal, Akshay IISER Bhopal Data Sci & Engn Bhopal India
Alteration in facial features can lead to a significant drop in recognition performance. These alterations can be due to several factors: one such prominent and less explored factor is illicit drug abuse. To advance t...
来源: 评论