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  • High-dimension Prototype is a Better Incremental Object Detection Learner
    To this end, we put forth a novel higher-dimension-prototype learning approach for KD-based IOD, enabling a more flexible, accurate, and fine-grained representation of feature distributions without the need to retain any previous task data
  • High-dimension Prototype is a Better Incremental Object Detection . . .
    To this end, we put forth a novel higher-dimension-prototype learning approach for KD-based IOD, enabling a more flexible, accurate, and fine-grained representation of feature distributions without the need to retain any previous task data
  • 论文介绍
    针对上述问题，本文提出了一种基于高维原型学习的增量目标检测方法。 具体贡献如下：（1）高维原型表示机制：提出高斯混合分布原型（GMDP），通过动态调整类分布原型的组件权重、均值和方差，更精确地刻画类内和类间差异，无需保留旧任务数据即可灵活表示特征分布，有效缓解知识偏移；（2）高维学习辅助策略：设计长度缩放渐进学习策略，通过逐步学习高维特征的判别性信息，降低复杂特征空间的学习难度；（3）原型可塑性增强机制：提出动态自适应原型优化（DAPO）策略，通过类间均值分散、类内组件聚合和原型方差最小化，提升原型的适应性与区分度。
  • High-Dimension Prototype Is a Better Incremental Object Detection . . .
    To this end, we put forth a novel higher-dimension-prototype learning approach for KD-based IOD, enabling a more flexible, accurate, and fine-grained representation of feature distributions without the need to retain any previous task data
  • High-dimension Prototype is a Better Incremental Object Detection . . .
    High-dimension Prototype is a Better Incremental Object Detection Learner In The Thirteenth International Conference on Learning Representations, ICLR 2025, Singapore, April 24-28, 2025
  • dblp: High-dimension Prototype is a Better Incremental Object Detection . . .
    Bibliographic details on High-dimension Prototype is a Better Incremental Object Detection Learner
  • High-dimension Prototype is a Better Incremental Object Detection . . .
    To this end, we put forth a novel higher-dimension-prototype learning approach for KD-based IOD, enabling a more flexible, accurate, and fine-grained representation of feature distributions without the need to retain any previous task data
  • High-dimension Prototype is a Better Incremental Object Detection . . .
    A cognitive architecture that expands its perceptual capabilities by generating object prototypes from user-provided natural language descriptions that are constructed using superellipsoid primitives, enabling structured and interpretable shape representations
  • High-dimension Prototype is a Better Incremental Object Detection Learner
    To this end, we put forth a novel higher-dimension-prototype learning approach for KD-based IOD, enabling a more flexible, accurate, and fine-grained representation of feature distributions without the need to retain any previous task data
  • 【创新突破】增量目标检测新纪元——iOD通过元学习重塑 . . .
    在此背景下，我们引入了一项革命性的解决方案——《Incremental Object Detection via Meta-Learning》 (iOD)，该论文已发表于IEEE Transactions on Pattern Analysis and Machine Intelligence（TPAMI）。





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