1 Paper Code HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection garfield-cpp/hgsfusion • • 16 Dec 2024 Hence, in this paper, we present the radar-camera fusion network with Hybrid Generation and Synchronization (HGSFusion), designed to better...
730 papers with code • 64 benchmarks • 63 datasets 3D Object Detection is a task in computer vision where the goal is to identify and locate objects in a 3D environment based on their shape, location, and orientation. It involves detecting the presence of objects and determining their ...
CVPR2022论文和代码整理:https://github.com/DWCTOD/CVPR2022-Papers-with-Code-Demo Updated on : 27 Apr 2022 total number : 4 Focal Sparse Convolutional Networks for 3D Object Detection 论文/Paper: http://arxiv.org/pdf/2204.12463 代码/Code: http://github.com/dvlab-research/FocalsConv 摘要: ...
Center-based 3D Object Detection and Tracking(CVPR2021) paper 3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection(CVPR2021) paper Embracing Single Stride 3D Object Detector with Sparse Transformer(CVPR2022) paper, code Point Density-Aware Voxels for LiDAR 3D Object Detection...
(多模态)MVX-Net: Multimodal VoxelNet for 3D Object Detection code: https://paperswithcode.com/paper/mvx-net-multimodal-voxelnet-for-3d-object 摘要:最近许多关于三维目标检测的工作都集中在设计可以消耗点云数据的神经网络架构上。虽然这些方法表现出令人鼓舞的性能,但它们通常基于单一模式,不...
However, there exists a distinct performance gap between multi-camera BEV and LiDAR based 3D object detection. One key reason is that LiDAR captures accurate depth and other geometry measurements, while it is notoriously challenging to infer such 3D information from merely image input. In this ...
with 85.15 mAPH (L2) detection performance. Further experiments validate the application of taking the place of human labels with such high-quality results. Our empirical study leads to rethinking conventions and interesting findings that can guide future research on offboard 3D object detection. ...
[24] Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Imagespaper|code Topic:具有全局上下文增强功能的自适应稀疏卷积网络可加快无人机图像上的目标检测速度 Absact:在资源受限的无人机平台上,低延迟无人机图像的目标检测是一项重要但具有挑战性的任务。本...
代码/Code: None MonoDTR: Monocular 3D Object Detection with Depth-Aware Transformer 论文/Paper: http://arxiv.org/pdf/2203.10981 代码/Code: None Unified Multivariate Gaussian Mixture for Efficient Neural Image Compression 论文/Paper: http://arxiv.org/pdf/2203.10897 ...
3D Object Detection Essay Reading 2024.04.01 Swin Transformer paper:https://arxiv.org/abs/2103.14030(ICCV 2021) code:https://github.com/microsoft/Swin-Transformer/blob/2622619f70760b60a42b996f5fcbe7c9d2e7ca57/models/swin_transformer.py#L458...