https://github.com/Cavendish518/SFPNet
공식 코드SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds
Papers with Code 아카이브
LIDAR Semantic Segmentation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/DeyvidKochanov-TomTom/kprnet
공식 코드KPRNet: Improving projection-based LiDAR semantic segmentation
https://github.com/GangZhang842/CPGNet
공식 코드CPGNet: Cascade Point-Grid Fusion Network for Real-Time LiDAR Semantic Segmentation
https://github.com/HuguesTHOMAS/KPConv
공식 코드KPConv: Flexible and Deformable Convolution for Point Clouds
https://github.com/ICEORY/PMF
공식 코드EPMF: Efficient Perception-aware Multi-sensor Fusion for 3D Semantic Segmentation
https://github.com/KangchengLiu/Feature-Geometric-Net-FG-Net
공식 코드https://github.com/OpenGVLab/PonderV2
공식 코드PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm
https://github.com/Pointcept/PointTransformerV2
공식 코드Point Transformer V2: Grouped Vector Attention and Partition-based Pooling
https://github.com/Pointcept/Pointcept
공식 코드Point Transformer V2: Grouped Vector Attention and Partition-based Pooling
https://github.com/QingyongHu/RandLA-Net
공식 코드RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds
https://github.com/Shathe/3D-MiniNet
공식 코드https://github.com/VisualComputingInstitute/DITR
공식 코드DINO in the Room: Leveraging 2D Foundation Models for 3D Segmentation
https://github.com/Xiangxu-0103/FRNet
공식 코드FRNet: Frustum-Range Networks for Scalable LiDAR Segmentation
https://github.com/aboulch/ConvPoint
공식 코드ConvPoint: Continuous Convolutions for Point Cloud Processing
https://github.com/alanwxz/nuc-net
공식 코드NUC-Net: Non-uniform Cylindrical Partition Network for Efficient LiDAR Semantic Segmentation
https://github.com/azhuantou/aiscene
공식 코드Exploring Scene Affinity for Semi-Supervised LiDAR Semantic Segmentation
https://github.com/cv-rits/coarse3d
공식 코드COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud Segmentation
https://github.com/dvlab-research/sphereformer
공식 코드https://github.com/dzcgaara/HuBo-VLM
공식 코드HuBo-VLM: Unified Vision-Language Model designed for HUman roBOt interaction tasks
https://github.com/edwardzhou130/PolarSeg
공식 코드PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation
https://github.com/engineerJPark/LiDAR-DataAug4Weather
공식 코드Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather
https://github.com/engineerjpark/lidarweather
공식 코드Rethinking Data Augmentation for Robust LiDAR Semantic Segmentation in Adverse Weather
https://github.com/facebookresearch/SparseConvNet
공식 코드3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
https://github.com/fengjiang5/knowledge-distillation-from-cylinder3d-to-polarnet
공식 코드Knowledge Distillation from 3D to Bird's-Eye-View for LiDAR Semantic Segmentation
https://github.com/fengluodb/lenet
공식 코드LENet: Lightweight And Efficient LiDAR Semantic Segmentation Using Multi-Scale Convolution Attention
https://github.com/fengzicai/lsk3dnet
공식 코드LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels
https://github.com/haibo-qiu/gfnet
공식 코드GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation
https://github.com/halbielee/ple
공식 코드Learning from Spatio-temporal Correlation for Semi-Supervised LiDAR Semantic Segmentation
https://github.com/huixiancheng/PCB-RandNet
공식 코드PCB-RandNet: Rethinking Random Sampling for LIDAR Semantic Segmentation in Autonomous Driving Scene
https://github.com/huixiancheng/cenet
공식 코드CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving
https://github.com/hzykent/lidal
공식 코드LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation
https://github.com/julessanchez/3dlabelprop
공식 코드https://github.com/jun-cen/cmdfusion
공식 코드https://github.com/jun-cen/open_world_3d_semantic_segmentation
공식 코드https://github.com/junbao-zhou/track-no-forgetting
공식 코드TeFF: Tracking-enhanced Forgetting-free Few-shot 3D LiDAR Semantic Segmentation
https://github.com/kazuto1011/dusty-gan-v2
공식 코드Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.