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3D Semantic Segmentation

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하위 태스크: 5
평가표: 19
보존된 평가 기록: 145

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/sunjiahao1999/spformer

공식 코드

Superpoint Transformer for 3D Scene Instance Segmentation

https://github.com/sunny599/aaai24-3dwssg-mma

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Multi-modality Affinity Inference for Weakly Supervised 3D Semantic Segmentation

https://github.com/suyanfei/DLA-Net

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DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point Clouds

https://github.com/tatarchm/tangent_conv

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Tangent Convolutions for Dense Prediction in 3D

https://github.com/tudelft3d/SUMS-Semantic-Urban-Mesh-Segmentation-public

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SUM: A Benchmark Dataset of Semantic Urban Meshes

https://github.com/tui-nicr/panoptic-mapping

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PanopticNDT: Efficient and Robust Panoptic Mapping

https://github.com/unmannedlab/RELLIS-3D

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RELLIS-3D Dataset: Data, Benchmarks and Analysis

https://github.com/ut-amrl/coda-devkit

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Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset

https://github.com/ut-amrl/coda-models

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Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset

https://github.com/valeoai/rangevit

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RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving

https://github.com/valeoai/slidr

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Image-to-Lidar Self-Supervised Distillation for Autonomous Driving Data

https://github.com/valeoai/ttyd

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Train Till You Drop: Towards Stable and Robust Source-free Unsupervised 3D Domain Adaptation

https://github.com/valeoai/waffleiron

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Using a Waffle Iron for Automotive Point Cloud Semantic Segmentation

https://github.com/valeoai/xmuda

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xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

https://github.com/valeoai/xmuda_journal

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Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation

https://github.com/vlar-group/growsp

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GrowSP: Unsupervised Semantic Segmentation of 3D Point Clouds

https://github.com/vlar-group/logosp

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LogoSP: Local-global Grouping of Superpoints for Unsupervised Semantic Segmentation of 3D Point Clouds

https://github.com/wangzy22/xmask3d

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XMask3D: Cross-modal Mask Reasoning for Open Vocabulary 3D Semantic Segmentation

https://github.com/wbhu/BPNet

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Bidirectional Projection Network for Cross Dimension Scene Understanding

https://github.com/weiguangzhao/BFANet

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BFANet: Revisiting 3D Semantic Segmentation with Boundary Feature Analysis

https://github.com/xheon/panoptic-reconstruction

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Panoptic 3D Scene Reconstruction From a Single RGB Image

https://github.com/xiaoaoran/FPS-Net

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FPS-Net: A Convolutional Fusion Network for Large-Scale LiDAR Point Cloud Segmentation

https://github.com/xiaoaoran/semanticstf

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3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds

https://github.com/xinge008/Cylinder3D

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Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation

https://github.com/xuxiaoxxxx/3DSS-VLG

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3D Weakly Supervised Semantic Segmentation with 2D Vision-Language Guidance

https://github.com/yangyangyang127/tfs3d

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Less is More: Towards Efficient Few-shot 3D Semantic Segmentation via Training-free Networks

https://github.com/yanx27/2dpass

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2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds

https://github.com/yanx27/JS3C-Net

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Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion

https://github.com/yhc2021/avs-net

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AVS-Net: Point Sampling with Adaptive Voxel Size for 3D Scene Understanding

https://github.com/yichen928/STRL

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Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds

https://github.com/yuhanghe01/hifanet

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Learning 3D Semantics from Pose-Noisy 2D Images with Hierarchical Full Attention Network

https://github.com/zaiweizhang/path_invariance_map_network

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Path-Invariant Map Networks

https://github.com/zeliu98/CloserLook3D

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A Closer Look at Local Aggregation Operators in Point Cloud Analysis

https://github.com/zhh6425/LocalContextPropagation

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LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers

https://github.com/zimingzhong/MeshSegmenter

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MeshSegmenter: Zero-Shot Mesh Semantic Segmentation via Texture Synthesis

https://github.com/zouzhenhong98/SensatUrban-BEV-Seg3D

공식 코드

Efficient Urban-scale Point Clouds Segmentation with BEV Projection

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