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检索条件"任意字段=Conference on Computer Vision and Pattern Recognition"
29687 条 记 录,以下是4681-4690 订阅
排序:
Florence-2: Advancing a Unified Representation for a Variety of vision Tasks
Florence-2: Advancing a Unified Representation for a Variety...
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conference on computer vision and pattern recognition (CVPR)
作者: Bin Xiao Haiping Wu Weijian Xu Xiyang Dai Houdong Hu Yumao Lu Michael Zeng Ce Liu Lu Yuan Microsoft
We introduce Florence-2, a novel vision foundation model with a unified, prompt-based representation for various computer vision and vision-language tasks. While existing large vision models excel in transfer learning... 详细信息
来源: 评论
PupilTAN: A Few-Shot Adversarial Pupil Localizer
PupilTAN: A Few-Shot Adversarial Pupil Localizer
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Poulopoulos, Nikolaos Psarakis, Emmanouil Z. Kosmopoulos, Dimitrios Univ Patras Comp Engn & Informat Patras Greece
The eye center localization is a challenging problem faced by many computer vision applications. The challenges typically stem from the scene variability, such as, the wide range of shapes, the lighting conditions, th... 详细信息
来源: 评论
Honeybee: Locality-Enhanced Projector for Multimodal LLM
Honeybee: Locality-Enhanced Projector for Multimodal LLM
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conference on computer vision and pattern recognition (CVPR)
作者: Junbum Cha Wooyoung Kang Jonghwan Mun Byungseok Roh Kakao Brain
In Multimodal Large Language Models (MLLMs), a visual projector plays a crucial role in bridging pre-trained vision encoders with LLMs, enabling profound visual understanding while harnessing the LLMs' robust capa... 详细信息
来源: 评论
On the Robustness of Monte Carlo Dropout Trained with Noisy Labels
On the Robustness of Monte Carlo Dropout Trained with Noisy ...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Goel, Purvi Li Chen Facebook Menlo Pk CA 94025 USA
The memorization effect of deep learning hinders its performance to effectively generalize on test set when learning with noisy labels. Prior study has discovered that epistemic uncertainty techniques are robust when ... 详细信息
来源: 评论
Partition-Guided GANs
Partition-Guided GANs
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Armandpour, Mohammadreza Sadeghian, Ali Li, Chunyuan Zhou, Mingyuan Texas A&M Univ College Stn TX 77843 USA Univ Florida Gainesville FL 32611 USA Microsoft Res Redmond WA USA Univ Texas Austin Austin TX 78712 USA
Despite the success of Generative Adversarial Networks (GANs), their training suffers from several well-known problems, including mode collapse and difficulties learning a disconnected set of manifolds. In this paper,... 详细信息
来源: 评论
FADES: Fair Disentanglement with Sensitive Relevance
FADES: Fair Disentanglement with Sensitive Relevance
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conference on computer vision and pattern recognition (CVPR)
作者: Taeuk Jang Xiaoqian Wang Purdue University West Lafayette IN USA
Learning fair representation in deep learning is essential to mitigate discriminatory outcomes and enhance trustworthiness. However, previous research has been commonly established on inappropriate assumptions prone t... 详细信息
来源: 评论
StyleCineGAN: Landscape Cinemagraph Generation Using a Pre-trained StyleGAN
StyleCineGAN: Landscape Cinemagraph Generation Using a Pre-t...
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conference on computer vision and pattern recognition (CVPR)
作者: Jongwoo Choi Kwanggyoon Seo Amirsaman Ashtari Junyong Noh Visual Media Lab KAIST
We propose a method that can generate cinemagraphs automatically from a still landscape image using a pre-trained StyleGAN. Inspired by the success of recent un-conditional video generation, we leverage a powerful pre... 详细信息
来源: 评论
Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation
Curriculum Graph Co-Teaching for Multi-Target Domain Adaptat...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Roy, Subhankar Krivosheev, Evgeny Zhong, Zhun Sebe, Nicu Ricci, Elisa Univ Trento Trento TN Italy Fdn Bruno Kessler Povo TN Italy
In this paper we address multi-target domain adaptation (MTDA), where given one labeled source dataset and multiple unlabeled target datasets that differ in data distributions, the task is to learn a robust predictor ... 详细信息
来源: 评论
NTIRE 2021 Multi-modal Aerial View Object Classification Challenge
NTIRE 2021 Multi-modal Aerial View Object Classification Cha...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Liu, Jerrick Inkawhich, Nathan Nina, Oliver Timofte, Radu Duan, Yuru Li, Gongzhe Geng, Xueli Cai, Huanqia Air Force Res Lab Albuquerque NM 87117 USA Univ Illinois Urbana IL 61801 USA Duke Univ Durham NC 27706 USA Swiss Fed Inst Technol Comp Vis Lab Zurich Switzerland Northwestern Polytech Univ Changan Campus Xian Shaanxi Peoples R China Beihang Univ Beijing Peoples R China Xidian Univ Key Lab Intelligent Percept & Image Understanding Xian Peoples R China Dengzhuang South Rd Beijing Peoples R China
In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with the NTIRE 2021 workshop at CVPR. This challenge is composed of two different tracks using EO... 详细信息
来源: 评论
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation
Encoding in Style: a StyleGAN Encoder for Image-to-Image Tra...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Richardson, Elad Alaluf, Yuval Patashnik, Or Nitzan, Yotam Azar, Yaniv Shapiro, Stav Cohen-Or, Daniel Penta AI Tel Aviv Israel Tel Aviv Univ Tel Aviv Israel
We present a generic image-to-image translation framework, pixel2style2pixel (pSp). Our pSp framework is based on a novel encoder network that directly generates a series of style vectors which are fed into a pretrain... 详细信息
来源: 评论