hispark-modelzoo-superpoint / model-card.json
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{
"name": "SuperPoint",
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"description": "SuperPoint模型的全卷积神经网络架构对全尺寸图像进行操作,并在单次前向传递中产生伴随固定长度描述符的兴趣点检测。该模型有一个单一的共享编码器来处理和减少输入图像的维数。在编码器之后,该架构分成两个解码器“头”,它们学习任务特定权重——一个用于兴趣点检测,另一个用于感兴趣点描述。大多数网络参数在两个任务之间共享,这与传统系统不同,传统系统首先检测兴趣点,然后计算描述符,并且缺乏跨两个任务共享计算和表示的能力。",
"category": "计算机视觉",
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"description": "SuperPoint模型的全卷积神经网络架构对全尺寸图像进行操作,并在单次前向传递中产生伴随固定长度描述符的兴趣点检测。该模型有一个单一的共享编码器来处理和减少输入图像的维数。在编码器之后,该架构分成两个解码器“头”,它们学习任务特定权重——一个用于兴趣点检测,另一个用于感兴趣点描述。大多数网络参数在两个任务之间共享,这与传统系统不同,传统系统首先检测兴趣点,然后计算描述符,并且缺乏跨两个任务共享计算和表示的能力。",
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