视觉网络的相关内容

YOLOv5改进 | 2023主干篇 | EfficientViT替换Backbone（高效的视觉变换网络）

一、本文介绍本文给大家带来的改进机制是EfficientViT（高效的视觉变换网络），EfficientViT的核心是一种轻量级的多尺度线性注意力模块，能够在只使用硬件高效操作的情况下实现全局感受野和多尺度学习。本文带来是2023年的最新版本的EfficientViT网络结构，论文题目是'Effi...

CVPR2021 | 视觉推理解释框架VRX：用结构化视觉概念作为解释网络推理逻辑的「语言」

大家好，我是Charmve。今天分享的一篇文章来自葛云皓，本文主要介绍了被 CVPR 2021 录用的文章《A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts》。本文提出...

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首篇！BEV-Locator：多目端到端视觉语义定位网络（清华&轻舟智航）（下）

实验和讨论nuScenes数据集结果NuScenes数据集包含城市地区的700个训练场景和150个测试场景，图像由6个环视摄像机拍摄。论文在nuScenes数据集上进行实验，以验证BEV定位器的有效性（用35个epoch训练）。论文从地图界面中提取地图元素。元素类型包括道路边界、车道分隔线和人行横道...

首篇！BEV-Locator：多目端到端视觉语义定位网络（清华&轻舟智航）（上）

摘要准确的定位能力是自动驾驶的基础。传统的视觉定位框架通过几何模型来解决语义地图匹配问题，几何模型依赖于复杂的参数调整，从而阻碍了大规模部署。本文提出了BEV定位器：一种使用多目相机图像的端到端视觉语义定位神经网络。具体地，视觉BEV（鸟瞰图）编码器提取多目图像并将其展平到BEV空间中。而语义地图特...

视觉神经网络模型优秀开源工作：PyTorch Image Models（timm）库（下）

1.4. 特征提取timm 提供了很多不同类型网络中间层的机制，其有助于作为特征提取以应用于下游任务.1.4.1. 最终特征图from PIL import Image import matplotlib.pyplot as plt import numpy as np import torch i...

视觉神经网络模型优秀开源工作：PyTorch Image Models（timm）库（上）

视觉神经网络模型优秀开源工作：PyTorch Image Models（timm）库PyTorchImageModels，简称timm，是一个巨大的PyTorch代码集合，包括了一系列：image modelslayersutilitiesoptimizersschedulersdata-loade...

ViTGAN：用视觉Transformer训练生成性对抗网络 Training GANs with Vision Transformers

> @[TOC](目录)ViTGAN是加州大学圣迭戈分校与 Google Research提出的一种用视觉Transformer来训练GAN的模型。该论文已被NIPS（Conference and Workshop on Neural Information Processing System...

【第26篇】MobileNets：用于移动视觉应用的高效卷积神经网络

MobileNets：用于移动视觉应用的高效卷积神经网络摘要我们提出了一类称为 MobileNets 的高效模型，用于移动和嵌入式视觉应用。 MobileNets 基于流线型架构，使用深度可分离卷积来构建轻量级深度神经网络。我们引入了两个简单的全局超参数，可以有效地在延迟和准确性之间进行权衡。这...

CVPR2021 | 视觉推理解释框架VRX：用结构化视觉概念作为解释网络推理逻辑的「语言」

本文主要介绍了被 CVPR 2021 录用的文章《A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts》。这项工作对神经网络推理逻辑的可解释性进行了探究：区分于大多数现有 ...

最前沿：视觉推理（Visual Reasoning），神经网络也可以有逻辑

在我们的上一篇文章最前沿：百家争鸣的Meta Learning/Learning to learn 中，我们谈到了星际2 需要AI具备极好的逻辑推理能力才行，那么实际上逻辑推理这个问题学术界一直有研究，但是进展缓慢。吴恩达Andrew Ng也说过当前的深度学习技术比较适合那些对...

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