这篇MMF(Multi-Task Multi-Sensor Fusion for 3D Object Detection[1])是Uber跟Toronto大学联合发布在CVPR2019的一篇关于利用多传感器(lidar+camera)融合进行物体识别的文章。 LiDAR跟Camera是自动驾驶车上非常常见的传感器,它们各自有自己的优缺点,例如: Camera 能够提供非常丰富的语义信息,而且能够看到很远的物体(例如...
论文链接:BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation 代码链接:github.com/mit-han-lab/ 作者:Zhijian Liu,Haotian Tang,Alexander Amini,Xinyu Yang,Huizi Mao,Daniela Rus,Song Han 发表单位:MIT、上海交通大学 会议/期刊:ICRA 2023 一、研究背景 自动驾驶系统上往...
BEVFusion的核心流程包括高效相机到BEV的转换、基于预计算和间隔减少的改进BEV pooling。通过将相机图像转换为BEV鸟瞰图，利用预计算技术提前计算视锥，仅在测试阶段估计深度值，从而得到3D坐标，大大提高了转换效率。同时，通过优化BEV pooling步骤，避免中间量的内存写入和无效计算，显著提高了处理速度。实验...
Provided are systems and methods that perform multi-task and/or multi-sensor fusion for three-dimensional object detection in furtherance of, for example, autonomous vehicle perception and control. In particular, according to one aspect of the present disclosure, example systems and methods described ...
[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation - J-xinyu/bevfusion
Implementation of Multi-Task Multi-Sensor Fusion for 3D Object Detection Introduction This project is a pytorch implementation of Multi-Task Multi-Sensor Fusion for 3D Object Detection paper, which is a end-to-end network to predict 3D bounding boxes using LIDAR point cloud and images. ...
The use of semantic segmentation technology to extract high-resolution remote sensing image object segmentation has important application prospects. With the rapid development of multi-sensor technology, the good complementary advantages between multimod
Dual AI camera setup with 13MP primary camera and a dedicated 2MP depth sensorthat creates depth effects to give you picture perfect portraits and beautiful bokehs More fun with more features! AI Scene Detection AI Portrait 5MP AI Selfie Camera 5MP AI selfie camera that intelligently detects...
Multicomponent gas mixture analysis using a single tin oxide sensor and dynamic pattern recognition A new method, which is based on the discrete wavelet transform, is presented for extracting important features from the response transients of micromachine... E Llobet,R Ionescu,S Al-Khalifa,... -...
论文提出了BEVFusion,在BEV的表示形式下对多模态的feature进行融合。如图c所示,在保证物体的几何结构不发生geometric distortion的同时,不损失语义信息。 Method BEVFusion主要关注multi-task(即同时进行detection和segmentation)下的多传感器融合。它的整体结构如下图 Efficient Camera-to-BEV Transformation Camera-to-BEV的...