| language: | |
| - zh | |
| tags: | |
| - hisilicon | |
| - hispark | |
| - npu | |
| - openharmony | |
| - modelzoo | |
| - pytorch | |
| # SuperPoint | |
| 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。 | |
| ## Mirror Metadata | |
| - Hugging Face repo: shadow-cann/hispark-modelzoo-superpoint | |
| - Portal model id: j3n1o7csso00 | |
| - Created at: 2026-03-16 21:11:02 | |
| - Updated at: 2026-03-26 09:35:38 | |
| - Category: 计算机视觉 | |
| ## Framework | |
| - PyTorch | |
| ## Supported OS | |
| - OpenHarmony | |
| - Linux | |
| ## Computing Power | |
| - Hi3403V100 SVP_NNN | |
| - Hi3403V100 NNN | |
| ## Tags | |
| - 特征点检测 | |
| ## Detail Parameters | |
| - 输入: 240x320 | |
| - 参数量: 1.24M | |
| - 计算量: 13.116GFLOPs | |
| ## Files In This Repo | |
| - superpoint_bs1_om-A8W8.om (编译模型 / A8W8) | |
| - superpoint_bs1.om (编译模型 / FP16; 编译模型 / OM 元数据 / A8W8) | |
| - superpoint_bs1.onnx (源模型 / 源模型下载; 源模型 / 源模型元数据) | |
| - superPointNet_170000_checkpoint.pth (源模型 / 源模型下载) | |
| - SVP_NNN_PC_V1.0.6.0.tgz (附加资源 / 附加资源) | |
| ## Upstream Links | |
| - Portal card: https://gitbubble.github.io/hisilicon-developer-portal-mirror/model-detail.html?id=j3n1o7csso00 | |
| - Upstream repository: https://gitee.com/HiSpark/modelzoo/tree/master/samples/built-in/point/SuperPoint | |
| - License reference: https://github.com/eric-yyjau/pytorch-superpoint/blob/master/LICENSE | |
| ## Notes | |
| - This repository was mirrored from the HiSilicon Developer Portal model card and local downloads captured on 2026-03-27. | |
| - File ownership follows the portal card mapping, not just filename similarity. | |
| - Cover image: 1702559012290562_cat_320x240_draw_keypoints.jpg | |