mlsanityData to 14 Oct 2026

Human-centric Scene Understanding for 3D Large-scale Scenarios

arXiv 2307.14392 ↗First posted 26 Jul 2023cs.CVcited by 17

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Abstract (arXiv)

Human-centric scene understanding is significant for real-world applications, but it is extremely challenging due to the existence of diverse human poses and actions, complex human-environment interactions, severe occlusions in crowds, etc. In this paper, we present a large-scale multi-modal dataset for human-centric scene understanding, dubbed HuCenLife, which is collected in diverse daily-life scenarios with rich and fine-grained annotations. Our HuCenLife can benefit many 3D perception tasks, such as segmentation, detection, action recognition, etc., and we also provide benchmarks for these tasks to facilitate related research. In addition, we design novel modules for LiDAR-based segmentation and action recognition, which are more applicable for large-scale human-centric scenarios and achieve state-of-the-art performance.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). Builds on 69 of its 79 references that are in the map. First posted on arXiv 26 Jul 2023.

Builds on

69 of 79 references.

References · 69

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
  3. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  4. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  5. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,523
  6. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  7. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,117
  8. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
  9. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,223
  10. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,715
  11. 2021ViViT: A Video Vision Transformercited by 1,620
  12. 2017VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detectioncited by 1,323
38 more
  1. 20194D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networkscited by 1,208
  2. 2019KPConv: Flexible and Deformable Convolution for Point Cloudscited by 1,205
  3. 2020Center-based 3D Object Detection and Trackingcited by 1,144
  4. 2018PointRCNN: 3D Object Proposal Generation and Detection from Point Cloudcited by 941
  5. 2019PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detectioncited by 891
  6. 20173D Semantic Segmentation with Submanifold Sparse Convolutional Networkscited by 748
  7. 2021Diffusion Probabilistic Models for 3D Point Cloud Generationcited by 735
  8. 2022EVA: Exploring the Limits of Masked Visual Representation Learning at Scalecited by 691
  9. 2016NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysiscited by 686
  10. 2019Deep Hough Voting for 3D Object Detection in Point Cloudscited by 648
  11. 20203DSSD: Point-based 3D Single Stage Object Detectorcited by 440
  12. 2022PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategiescited by 436
  13. 2020Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detectioncited by 410
  14. 2020Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentationcited by 389
  15. 2022Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Frameworkcited by 379
  16. 2020PointGroup: Dual-Set Point Grouping for 3D Instance Segmentationcited by 321
  17. 2019STD: Sparse-to-Dense 3D Object Detector for Point Cloudcited by 282
  18. 2020PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentationcited by 275
  19. 2022BEHAVE: Dataset and Method for Tracking Human Object Interactionscited by 249
  20. 2017SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloudcited by 232
  21. 2022SoftGroup for 3D Instance Segmentation on Point Cloudscited by 200
  22. 2020OccuSeg: Occupancy-aware 3D Instance Segmentationcited by 177
  23. 2019Learning Object Bounding Boxes for 3D Instance Segmentation on Point Cloudscited by 156
  24. 2022Multiview Transformers for Video Recognitioncited by 148
  25. 2018GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloudcited by 146
  26. 20203D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentationcited by 141
  27. 2021RangeDet:In Defense of Range View for LiDAR-based 3D Object Detectioncited by 140
  28. 2022Not All Points Are Equal: Learning Highly Efficient Point-based Detectors for 3D LiDAR Point Cloudscited by 131
  29. 2021Hierarchical Aggregation for 3D Instance Segmentationcited by 127
  30. 2019Fast Point R-CNNcited by 119
  31. 2022UniFormerV2: Spatiotemporal Learning by Arming Image ViTs with Video UniFormercited by 116
  32. 2022Superpoint Transformer for 3D Scene Instance Segmentationcited by 116
  33. 2021RSN: Range Sparse Net for Efficient, Accurate LiDAR 3D Object Detectioncited by 115
  34. 2021Multimodal Trajectory Prediction Conditioned on Lane-Graph Traversalscited by 113
  35. 2018TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agentscited by 111
  36. 2022CenterFormer: Center-based Transformer for 3D Object Detectioncited by 99
  37. 2022Learning to Generate Realistic LiDAR Point Cloudscited by 93
  38. 2020LiDAR-based Panoptic Segmentation via Dynamic Shifting Networkcited by 84

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 10; 2025: 1; 2026: 3.

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  1. 2023UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebasecited by 57
  2. 2024RealDex: Towards Human-like Grasping for Robotic Dexterous Handcited by 34
  3. 2024Language-driven Grasp Detectioncited by 26
  4. 2024Adapting to Length Shift: FlexiLength Network for Trajectory Predictioncited by 22
  5. 2023Learning to Adapt SAM for Segmenting Cross-domain Point Cloudscited by 20
  6. 2024LiveHPS: LiDAR-based Scene-level Human Pose and Shape Estimation in Free Environmentcited by 20
  7. 2024LiveHPS++: Robust and Coherent Motion Capture in Dynamic Free Environmentcited by 6
  8. 2023Model2Scene: Learning 3D Scene Representation via Contrastive Language-CAD Models Pre-trainingcited by 3
  9. 2024A Unified Framework for Human-centric Point Cloud Video Understandingcited by 3
  10. 2024FreeCap: Hybrid Calibration-Free Motion Capture in Open Environmentscited by 3
  11. 2024PanoSLAM: Panoptic 3D Scene Reconstruction via Gaussian SLAMcited by 3
  12. 2024HUNTER: Unsupervised Human-centric 3D Detection via Transferring Knowledge from Synthetic Instances to Real Scenescited by 2
5 more
  1. 2024Towards Practical Human Motion Prediction with LiDAR Point Cloudscited by 2
  2. 2025DeSPITE: Exploring Contrastive Deep Skeleton-Pointcloud-IMU-Text Embeddings for Advanced Point Cloud Human Activity Understandingcited by 1
  3. 2026SHOE: Semantic HOI Open-Vocabulary Evaluation Metriccited by 1
  4. 2026CausalGS: Learning Physical Causality of 3D Dynamic Scenes with Gaussian Representationscited by 0
  5. 2026Sen-Cap: Sensor-Flexible and Noise-Resilient Human Motion Capture via LiDAR-Camera Integrationcited by 0