https://github.com/facebookresearch/ContrastiveSceneContexts
공식 코드Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts
Papers with Code 아카이브
3D Semantic Segmentation
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3D Semantic Segmentation is a computer vision task that involves dividing a 3D point cloud or 3D mesh into semantically meaningful parts or regions. The goal of 3D semantic segmentation is to identify and label different objects and parts within a 3D scene, which can be used for applications such as robotics, autonomous driving, and augmented reality.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/facebookresearch/SparseConvNet
공식 코드3D Semantic Segmentation with Submanifold Sparse Convolutional Networks
https://github.com/facebookresearch/sonata
공식 코드Sonata: Self-Supervised Learning of Reliable Point Representations
https://github.com/fatemeh-ma/covered-a-dataset-for-3d-semantic-segmentation
공식 코드COVERED, CollabOratiVE Robot Environment Dataset for 3D Semantic segmentation
https://github.com/fayeben/adas
공식 코드UniDA3D: Unified Domain Adaptive 3D Semantic Segmentation Pipeline
https://github.com/fcendra/sl3d
공식 코드https://github.com/fengzicai/lsk3dnet
공식 코드LSK3DNet: Towards Effective and Efficient 3D Perception with Large Sparse Kernels
https://github.com/fengzicai/s2s
공식 코드Shape2Scene: 3D Scene Representation Learning Through Pre-training on Shape Data
https://github.com/fitushar/Brain-Tissue-Segmentation-Using-Deep-Learning-Pipeline-NeuroNet
공식 코드Brain Tissue Segmentation Using NeuroNet With Different Pre-processing Techniques
https://github.com/goblin327/segstitch
공식 코드SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging Segmentation
https://github.com/guochengqian/openpoints/blob/master/models/backbone/pointvector.py
공식 코드PointVector: A Vector Representation In Point Cloud Analysis
https://github.com/guochengqian/pointnext
공식 코드PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
https://github.com/haibo-qiu/gfnet
공식 코드GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation
https://github.com/hama-dl-dev/sesame
공식 코드SeSame: Simple, Easy 3D Object Detection with Point-Wise Semantics
https://github.com/hancyran/RPNet
공식 코드https://github.com/hancyran/RepSurf
공식 코드https://github.com/haydenyu/mm-point
공식 코드MM-Point: Multi-View Information-Enhanced Multi-Modal Self-Supervised 3D Point Cloud Understanding
https://github.com/hkust-vgd/shellnet
공식 코드ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics
https://github.com/huixiancheng/cenet
공식 코드CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for Autonomous Driving
https://github.com/hzykent/JSENet
공식 코드JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds
https://github.com/hzykent/VMNet
공식 코드VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation
https://github.com/ignf/myria3d
공식 코드https://github.com/ignf/pacasam
공식 코드https://github.com/isunLt/IUPC
공식 코드Image Understands Point Cloud: Weakly Supervised 3D Semantic Segmentation via Association Learning
https://github.com/jackd/template_ffd
공식 코드Learning Free-Form Deformations for 3D Object Reconstruction
https://github.com/jialeli1/lidarseg3d
공식 코드MSeg3D: Multi-modal 3D Semantic Segmentation for Autonomous Driving
https://github.com/joaopcbertoldo/tomo2seg
공식 코드A modular U-Net for automated segmentation of X-ray tomography images in composite materials
https://github.com/jokester-zzz/ssa-sc
공식 코드Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds
https://github.com/julessanchez/3dlabelprop
공식 코드Domain generalization of 3D semantic segmentation in autonomous driving
https://github.com/julessanchez/coarselabel
공식 코드COLA: COarse LAbel pre-training for 3D semantic segmentation of sparse LiDAR datasets
https://github.com/kleinzcy/SASSnet
공식 코드Shape-aware Semi-supervised 3D Semantic Segmentation for Medical Images
https://github.com/kumuji/mix3d
공식 코드https://github.com/l1997i/DurLAR
공식 코드On Deep Learning for Geometric and Semantic Scene Understanding Using On-Vehicle 3D LiDAR
https://github.com/l1997i/lim3d
공식 코드Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic Segmentation
https://github.com/l1997i/rapid_seg
공식 코드RAPiD-Seg: Range-Aware Pointwise Distance Distribution Networks for 3D LiDAR Segmentation
https://github.com/ldkong1205/Robo3D
공식 코드Robo3D: Towards Robust and Reliable 3D Perception against Corruptions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.