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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351-360 订阅
排序:
TransNeXt: Robust Foveal Visual Perception for vision Transformers
TransNeXt: Robust Foveal Visual Perception for Vision Transf...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Shi, Dai
Due to the depth degradation effect in residual connections, many efficient vision Transformers models that rely on stacking layers for information exchange often fail to form sufficient information mixing, leading to... 详细信息
来源: 评论
Align before Adapt: Leveraging Entity-to-Region Alignments for Generalizable Video Action recognition
Align before Adapt: Leveraging Entity-to-Region Alignments f...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Chen, Yifei Chen, Dapeng Liu, Ruijin Zhou, Sai Xue, Wenyuan Peng, Wei Huawei Technol IT Innovat & Res Ctr Shenzhen Peoples R China
Large-scale visual-language pre-trained models have achieved significant success in various video tasks. However, most existing methods follow an adapt then align paradigm, which adapts pre-trained image encoders to m... 详细信息
来源: 评论
HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data
HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual I...
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Yu, Qifan Li, Juncheng Wei, Longhui Pang, Liang Ye, Wentao Qin, Bosheng Tang, Siliang Tian, Qi Zhuang, Yueting Zhejiang Univ Hangzhou Peoples R China Huawei Cloud Suzhou Peoples R China Chinese Acad Sci Inst Comp Technol Beijing Peoples R China
Multi-modal Large Language Models (MLLMs) tuned on machine-generated instruction-following data have demonstrated remarkable performance in various multi-modal understanding and generation tasks. However, the hallucin... 详细信息
来源: 评论
Continual Forgetting for Pre-trained vision Models
Continual Forgetting for Pre-trained Vision Models
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhao, Hongbo Ni, Bolin Fang, Junsong Wang, Yuxi Chen, Yuntao Meng, Gaofeng Zhang, Zhaoxiang Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence Beijing Peoples R China Chinese Acad Sci Ctr Artificial Intelligence & Robot Hong Kong Inst Sci & Innovat Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Shanghai Artificial Intelligence Lab Shanghai Peoples R China
For privacy and security concerns, the need to erase unwanted information from pre-trained vision models is becoming evident nowadays. In real-world scenarios, erasure requests originate at any time from both users an... 详细信息
来源: 评论
On Scaling up a Multilingual vision and Language Model
On Scaling up a Multilingual Vision and Language Model
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Chen, Xi Djolonga, Josip Padlewski, Piotr Mustafa, Basil Changpinyo, Soravit Wu, Jialin Ruiz, Carlos Riquelme Goodman, Sebastian Wang, Xiao Tay, Yi Shakeri, Siamak Dehghani, Mostafa Salz, Daniel Lucic, Mario Tschannen, Michael Nagrani, Arsha Hu, Hexiang Joshi, Mandar Pang, Bo Montgomery, Ceslee Pietrzyk, Paulina Ritter, Marvin Piergiovanni, A. J. Minderer, Matthias Pavetic, Filip Waters, Austin Li, Gang Alabdulmohsin, Ibrahim Beyer, Lucas Amelot, Julien Lee, Kenton Steiner, Andreas Peter Li, Yang Keysers, Daniel Arnab, Anurag Xu, Yuanzhong Rong, Keran Kolesnikov, Alexander Seyedhosseini, Mojtaba Angelova, Anelia Zhai, Xiaohua Houlsby, Neil Soricut, Radu Google Mountain View CA 94043 USA
We explore the boundaries of scaling up a multilingual vision and language model, both in terms of size of the components and the breadth of its training task mixture. Our model achieves new levels of performance on a... 详细信息
来源: 评论
Learning from Observer Gaze: Zero-Shot Attention Prediction Oriented by Human-Object Interaction recognition
Learning from Observer Gaze: Zero-Shot Attention Prediction ...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhou, Yuchen Liu, Linkai Gou, Chao Sun Yat Sen Univ Guangzhou Peoples R China
Most existing attention prediction research focuses on salient instances like humans and objects. However, the more complex interaction-oriented attention, arising from the comprehension of interactions between instan... 详细信息
来源: 评论
Exploring and Utilizing pattern Imbalance
Exploring and Utilizing Pattern Imbalance
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Mei, Shibin Zhao, Chenglong Yuan, Shengchao Ni, Bingbing Shanghai Jiao Tong Univ Shanghai 200240 Peoples R China
In this paper, we identify pattern imbalance from several aspects, and further develop a new training scheme to avert pattern preference as well as spurious correlation. In contrast to prior methods which are mostly c... 详细信息
来源: 评论
Pre-training vision Models with Mandelbulb Variations
Pre-training Vision Models with Mandelbulb Variations
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Chiche, Benjamin Naoto Horikawa, Yuto Fujita, Ryo Rist Inc 830 Hongakujimae-ChoGojo-DoriShimogyo-Ku Kyoto 6008102 Japan
The use of models that have been pre-trained on natural image datasets like ImageNet may face some limitations. First, this use may be restricted due to copyright and license on the training images, and privacy laws. ... 详细信息
来源: 评论
Adapting Short-Term Transformers for Action Detection in Untrimmed Videos
Adapting Short-Term Transformers for Action Detection in Unt...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Yang, Min Gao, Huan Guo, Ping Wang, Limin Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Inchitech Beijing Peoples R China Intel Labs China Hillsboro OR USA Shanghai AI Lab Shanghai Peoples R China
vision Transformer (ViT) has shown high potential in video recognition, owing to its flexible design, adaptable self-attention mechanisms, and the efficacy of masked pretraining. Yet, it remains unclear how to adapt t... 详细信息
来源: 评论
EvDiG: Event-guided Direct and Global Components Separation
EvDiG: Event-guided Direct and Global Components Separation
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Zhou, Xinyu Duan, Peiqi Li, Boyu Zhou, Chu Xu, Chao Shi, Boxin Peking Univ Sch Intelligence Sci & Technol Natl Key Lab Gen AI Beijing Peoples R China Peking Univ Sch Comp Sci Natl Key Lab Multimedia Informat Proc Beijing Peoples R China Peking Univ Sch Comp Sci Natl Engn Res Ctr Visual Technol Beijing Peoples R China
Separating the direct and global components of a scene aids in shape recovery and basic material understanding. Conventional methods capture multiple frames under high frequency illumination patterns or shadows, requi... 详细信息
来源: 评论