Hybrid detectors :如center point,SECOND, 同时使用dense feature和sparse feature。 Sparse detectors :如VoxelNeXt,只使用saprse feature。 Sparse convolutions 3d检测算法为了提高计算效率,通常会使用稀疏卷积对数据进行处理。常用的稀疏卷积有两种: 1.submanifold sparse convolution:能够保留input feature map和output ...
BACKBONE_3D BACKBONE_3D: NAME: VoxelResBackBone8xVoxelNeXt2D 论文采用的sparse CNN backbone network有6层,比常规的backbone多了两层,即Method中的Additional Down-sampling,以获得更大的感受野。 self.conv1 = spconv.SparseSequential( SparseBasicBlock(32, 32, norm_fn=norm_fn, indice_key='res1'), Spa...
fully sparse detectors to solve this issue; nevertheless, the resulting models either rely on a complex multi-stage pipeline or exhibit inferior performance. In this work, we propose SAFDNet, a straightforward yet highly effective architecture, tailored for fully sparse 3D object detection. In SAFD...
Notably, on Argoverse2, SAFDNet surpassed the previous best hybrid detector HEDNet by 2.6% mAP while being 2.1x faster, and yielded 2.1% mAP gains over the previous best sparse detector FSDv2 while being 1.3x faster. The code will be available at this https URL . 展开 ...
Embracing Single Stride 3D Object Detector with Sparse Transformer(CVPR 2022). Fully Sparse 3D Object Detection(NeurIPS 2022). Super Sparse 3D Object Detection(TPAMI 2023). Once Detected, Never Lost: Surpassing Human Performance in Offline LiDAR based 3D Object Detection(ICCV 2023, Oral). ...
This is the official implementation ofVoxelNeXt(CVPR 2023). VoxelNeXt is a clean, simple, and fully-sparse 3D object detector. The core idea is to predict objects directly upon sparse voxel features. No sparse-to-dense conversion, anchors, or center proxies are needed anymore. For more detail...
OBELISK-Net: Fewer Layers to Solve 3D Multi-Organ Segmentation with Sparse Deformable Convolutions We propose a novel and effective method based on trainable 3D convolution kernels that learns both filter coefficients and spatial filter offsets in a ... MP Heinrich,O Oktay,N Bouteldja - 《Medic...
A multi-modal exploration on the paradigm of fully sparse 3D object detection Installation First initialize the conda environment conda create -n FSF python=3.8 -y conda activate FSF pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 torchaudio==0.9.0 -f https://download.pytorch.org/...
Sparse 3d topological graphs for micro-aerial vehicle planning[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018: 1-9. 微型飞行器路径规划的稀疏 3D 拓扑图 苏黎世联邦理工;作者主页;路径规划与建图部分代码开源,相关论文: Oleynikova H, Taylor Z, ...
Codes for “Fully Sparse 3D Object Detection” & “Embracing Single Stride 3D Object Detector with Sparse Transformer” - zhouleidcc/SST