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检索条件"机构=Shanghai Key Lab of Intelligent Information Processing and School of Computer Science"
1784 条 记 录,以下是111-120 订阅
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PHT-CAD: Efficient CAD Parametric Primitive Analysis with Progressive Hierarchical Tuning
arXiv
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arXiv 2025年
作者: Niu, Ke Chen, Yuwen Yu, Haiyang Chen, Zhuofan Que, Xianghui Li, Bin Xue, Xiangyang Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University China
computer-Aided Design (CAD) plays a pivotal role in industrial manufacturing, yet 2D Parametric Primitive Analysis (PPA) remains underexplored due to two key challenges: structural constraint reasoning and advanced se... 详细信息
来源: 评论
Diabetic Retinopathy Grading with Weakly-Supervised Lesion Priors  48
Diabetic Retinopathy Grading with Weakly-Supervised Lesion P...
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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023
作者: Hou, Junlin Xiao, Fan Xu, Jilan Feng, Rui Zhang, Yuejie Zou, Haidong Lu, Lina Xue, Wenwen Fudan University School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai China Fudan University Academy for Engineering and Technology Shanghai China Shanghai Eye Diseases Prevention & Treatment Center Shanghai China
Explicit information of lesions can provide visual instructions for diabetic retinopathy (DR) grading on fundus images. However, pixel-level lesion annotations are extremely difficult and time-consuming to acquire. In... 详细信息
来源: 评论
Detecting compromised accounts caused by phone number recycling on e-commerce platforms: taking Meituan as an example
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Frontiers of information Technology & Electronic Engineering 2024年 第8期25卷 1077-1095页
作者: Min GAO Shutong CHEN Yangbo GAO Zhenhua ZHANG Yu CHEN Yupeng LI Qiongzan YE Xin WANG Yang CHEN School of Computer Science Fudan UniversityShanghai 200438China Shanghai Key Lab of Intelligent Information Processing Fudan UniversityShanghai 200438China Meituan Beijing 100005China Department of Interactive Media Hong Kong Baptist UniversityHong Kong 999077China
Phone number recycling(PNR)refers to the event wherein a mobile operator collects a disconnected number and reassigns it to a new *** has posed a threat to the reliability of the existing authentication solution for e... 详细信息
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A Multitask Learning Approach for Chinese National Instruments Recognition and Timbre Space Regression  9th
A Multitask Learning Approach for Chinese National Instrumen...
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9th Conference on Sound and Music Technology, CSMT 2021
作者: Xu, Shenyang Jiang, Yiliang Li, Zijin Sun, Xiaoheng Li, Wei Central Conservatory of Music Beijing100031 China School of Computer Science and Technology Fudan University Shanghai200438 China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai200433 China
Musical instrument recognition is an essential task in the domain of music information retrieval. So far, most existing research are focused on western instruments. In this research, we turn to Chinese national instru... 详细信息
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BERTScore is Unfair: On Social Bias in Language Model-Based Metrics for Text Generation
BERTScore is Unfair: On Social Bias in Language Model-Based ...
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2022 Conference on Empirical Methods in Natural Language processing, EMNLP 2022
作者: Sun, Tianxiang He, Junliang Qiu, Xipeng Huang, Xuanjing School of Computer Science Fudan University China Shanghai Key Laboratory of Intelligent Information Processing Fudan University China
Automatic evaluation metrics are crucial to the development of generative systems. In recent years, pre-trained language model (PLM) based metrics, such as BERTScore (Zhang et al., 2020), have been commonly adopted in... 详细信息
来源: 评论
Late Prompt Tuning: A Late Prompt Could Be Better Than Many Prompts
Late Prompt Tuning: A Late Prompt Could Be Better Than Many ...
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2022 Findings of the Association for Computational Linguistics: EMNLP 2022
作者: Liu, Xiangyang Sun, Tianxiang Huang, Xuanjing Qiu, Xipeng School of Computer Science Fudan University China Shanghai Key Laboratory of Intelligent Information Processing Fudan University China
Prompt tuning is a parameter-efficient tuning (PETuning) method for utilizing pre-trained models (PTMs) that simply prepends a soft prompt to the input and only optimizes the prompt to adapt PTMs to downstream tasks. ... 详细信息
来源: 评论
FacialFlowNet: Advancing Facial Optical Flow Estimation with a Diverse Dataset and a Decomposed Model
arXiv
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arXiv 2024年
作者: Lu, Jianzhi He, Ruian Zhou, Shili Tan, Weimin Yan, Bo Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai China
Facial movements play a crucial role in conveying altitude and intentions, and facial optical flow provides a dynamic and detailed representation of it. However, the scarcity of datasets and a modern baseline hinders ... 详细信息
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RankDNN: Learning to Rank for Few-Shot Learning  37
RankDNN: Learning to Rank for Few-Shot Learning
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37th AAAI Conference on Artificial Intelligence, AAAI 2023
作者: Guo, Qianyu Haotong, Gong Wei, Xujun Fu, Yanwei Yu, Yizhou Zhang, Wenqiang Ge, Weifeng Nebula AI Group School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Intelligent Information Processing Shanghai China Academy for Engineering & Technology Fudan University Shanghai China Department of Computer Science The University of Hong Kong Hong Kong
This paper introduces a new few-shot learning pipeline that casts relevance ranking for image retrieval as binary ranking relation classification. In comparison to image classification, ranking relation classification... 详细信息
来源: 评论
Facial Micro-Motion-Aware Mixup for Micro-Expression Recognition
Facial Micro-Motion-Aware Mixup for Micro-Expression Recogni...
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International Conference on Acoustics, Speech, and Signal processing (ICASSP)
作者: Zhuoyao Gu Miao Pang Zhen Xing Weimin Tan Xuhao Jiang Bo Yan School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China
Data-driven learning models have demonstrated strong benefits in capturing subtle facial movements for micro-expression recognition (MER), but are limited by the available data. Generative models can generate a variet...
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GenRec: Unifying Video Generation and Recognition with Diffusion Models  38
GenRec: Unifying Video Generation and Recognition with Diffu...
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38th Conference on Neural information processing Systems, NeurIPS 2024
作者: Weng, Zejia Yang, Xitong Xing, Zhen Wu, Zuxuan Jiang, Yu-Gang Shanghai Key Lab of Intell. Info. Processing School of CS Fudan University China Shanghai Collaborative Innovation Center of Intelligent Visual Computing China Department of Computer Science University of Maryland United States
Video diffusion models are able to generate high-quality videos by learning strong spatial-temporal priors on large-scale datasets. In this paper, we aim to investigate whether such priors derived from a generative pr...
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