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Towards a Definition of Disentangled Representations

Towards a Definition of Disentangled Representations Irina Higgins∗ , David Amos∗ , David Pfau, Sebastien

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Towards biologically plausible deep learning

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    Towards Precise Supervision of Feature Super-Resolution

    虽然最近基于proposal的CNN模型在目标检测方面取得了成功,但是由于小兴趣区域(small region of interest, RoI)所包含的信息有...

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    MOT:Towards Real-Time Multi-Object Tracking

    简介 Towards Real-Time Multi-Object Tracking是一个online的多目标跟踪(MOT)算法,基于TBD(Traking-by-Detection)的策略,在之前的MOT 而《Towards Real-Time Multi-Object Tracking》中将detection model和embedding model整合为一个模型,即Joint Detection and Embedding (JDE) model,所以我们用JDE作为《Towards Real-Time Multi-Object Tracking》的简称。 《Towards Real-Time Multi-Object Tracking》原理 contributions JDE核心思想是一种联合检测和嵌入向量的模型,即Joint Detection

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    车牌识别--Towards End-to-End License Plate Detection and Recognition

    https://blog.csdn.net/zhangjunhit/article/details/82627163 Towards End-to-End License Plate Detection

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    量化网络训练--Towards Effective Low-bitwidth Convolutional Neural Networks

    https://blog.csdn.net/zhangjunhit/article/details/89487706 Towards Effective Low-bitwidth Convolutional

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    MOT:Towards Real-Time Multi-Object Tracking

    简介 《Towards Real-Time Multi-Object Tracking》是一个online的多目标跟踪(MOT)算法,基于TBD(Traking-by-Detection)的策略,在之前的 而《Towards Real-Time Multi-Object Tracking》中将detection model和embedding model整合为一个模型,即Joint Detection and Embedding (JDE) model,所以我们用JDE作为《Towards Real-Time Multi-Object Tracking》的简称。 《Towards Real-Time Multi-Object Tracking》原理 contributions ?

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    大角度人脸转正--Towards Large-Pose Face Frontalization in the Wild

    Towards Large-Pose Face Frontalization in the Wild ICCV2017 https://www.arxiv.org/abs/1704.06244

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    密码学安全归约7 Analysis(Towards A Correct Reduction)

    密码学安全归约7 Analysis(Towards A Correct Reduction) 目前郭老师就在B站录了7节课,终于补完啦。学习的思路更清晰了。今后继续先刷完slide,再继续刷书。

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    人车密度估计--Towards perspective-free object counting with deep learning

    Towards perspective-free object counting with deep learning ECCV2016 https://github.com/gramuah/

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    Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

    最先进的目标检测网络依赖于区域建议算法来假设目标位置。SPPnet和Faster R-CNN等技术的进步,降低了检测网络的运行时间,但是暴露了区域提案计算的瓶颈...

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    视频动作识别--Temporal Segment Networks: Towards Good Practices for Deep Action Recognition

    Temporal Segment Networks: Towards Good Practices for Deep Action Recognition ECCV2016 https://github.com

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    视频动作识别--Towards Good Practices for Very Deep Two-Stream ConvNets

    Towards Good Practices for Very Deep Two-stream ConvNets http://yjxiong.me/others/action_recog/ https

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    车道线检测--Towards End-to-End Lane Detection: an Instance Segmentation Approach

    https://blog.csdn.net/zhangjunhit/article/details/89531619 Towards End-to-End Lane Detection:

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    【AIDL专栏】罗杰波: Computer Vision ++: The Next Step Towards Big AI

    美国罗切斯特大学教授罗杰波作了题为《Computer Vision ++: The Next Step Towards Big AI》的报告。

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    Towards Open World Object Detection -CVPR2021 Oral(开放世界中的目标检测)

    首先基于一个现象:人类在对事物进行观察的时候,是能够检测到每个实例,并按照自己已知的知识来对每个实例进行分类,有认知的归属到对应类别,无认知的归属到未知(unk...

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    文献阅读:Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning

    文献阅读:Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning 1.

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    小白也能看懂的BP反向传播算法之Towards-Backpropagation

    想要理解backpropagation反向传播算法,就必须先理解微分!本文会以一个简单的神经元的例子来讲解backpropagation反向传播算法中的微分的概...

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    车牌检测识别--Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks

    Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks https://arxiv.org

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    Good Feature Matching: Towards Accurate, Robust VOVSLAM with Low Latency 良好的特征匹配:实现准确、鲁棒的低延迟VOVSLA

    Good Feature Matching: Towards Accurate, Robust VO/VSLAM with Low Latency 良好的特征匹配:实现准确、鲁棒的低延迟VO/VSLAM

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