mlsanityData to 7 Oct 2026

LiCROcc: Teach Radar for Accurate Semantic Occupancy Prediction using LiDAR and Camera

arXiv 2407.16197 ↗First posted 23 Jul 2024cs.CV cs.ROcited by 18

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Abstract (arXiv)

Semantic Scene Completion (SSC) is pivotal in autonomous driving perception, frequently confronted with the complexities of weather and illumination changes. The long-term strategy involves fusing multi-modal information to bolster the system's robustness. Radar, increasingly utilized for 3D target detection, is gradually replacing LiDAR in autonomous driving applications, offering a robust sensing alternative. In this paper, we focus on the potential of 3D radar in semantic scene completion, pioneering cross-modal refinement techniques for improved robustness against weather and illumination changes, and enhancing SSC performance.Regarding model architecture, we propose a three-stage tight fusion approach on BEV to realize a fusion framework for point clouds and images. Based on this foundation, we designed three cross-modal distillation modules-CMRD, BRD, and PDD. Our approach enhances the performance in both radar-only (R-LiCROcc) and radar-camera (RC-LiCROcc) settings by distilling to them the rich semantic and structural information of the fused features of LiDAR and camera. Finally, our LC-Fusion (teacher model), R-LiCROcc and RC-LiCROcc achieve the best performance on the nuScenes-Occupancy dataset, with mIOU exceeding the baseline by 22.9%, 44.1%, and 15.5%, respectively. The project page is available at https://hr-zju.github.io/LiCROcc/.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 43 of its 49 references that are in the map. First posted on arXiv 23 Jul 2024.

Builds on

43 of 49 references.

References · 43

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2015Distilling the Knowledge in a Neural Networkcited by 10,076
  3. 2017Decoupled Weight Decay Regularizationcited by 1,722
  4. 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,040
  5. 2016Semantic Scene Completion from a Single Depth Imagecited by 468
  6. 2023Tri-Perspective View for Vision-Based 3D Semantic Occupancy Predictioncited by 404
  7. 2021MonoScene: Monocular 3D Semantic Scene Completioncited by 357
  8. 2023OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Predictioncited by 287
  9. 2020Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completioncited by 222
  10. 2023OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perceptioncited by 218
  11. 2020LMSCNet: Lightweight Multiscale 3D Semantic Completioncited by 187
  12. 2020CenterFusion: Center-based Radar and Camera Fusion for 3D Object Detectioncited by 159
31 more
  1. 20222DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Cloudscited by 157
  2. 2020Anisotropic Convolutional Networks for 3D Semantic Scene Completioncited by 126
  3. 20203D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Priorcited by 124
  4. 2022Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentationcited by 118
  5. 2023PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentationcited by 114
  6. 2020S3CNet: A Sparse Semantic Scene Completion Network for LiDAR Point Cloudscited by 102
  7. 2023FlashOcc: Fast and Memory-Efficient Occupancy Prediction via Channel-to-Height Plugincited by 101
  8. 2023CRN: Camera Radar Net for Accurate, Robust, Efficient 3D Perceptioncited by 81
  9. 2023SCPNet: Semantic Scene Completion on Point Cloudcited by 80
  10. 2020Semantic Scene Completion using Local Deep Implicit Functions on LiDAR Datacited by 74
  11. 2019Efficient Semantic Scene Completion Network with Spatial Group Convolutioncited by 66
  12. 2022CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformercited by 66
  13. 2022BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object Detectioncited by 66
  14. 2023LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusioncited by 57
  15. 2023PointOcc: Cylindrical Tri-Perspective View for Point-based 3D Semantic Occupancy Predictioncited by 51
  16. 2024FastOcc: Accelerating 3D Occupancy Prediction by Fusing the 2D Bird's-Eye View and Perspective Viewcited by 51
  17. 2022Bridging the View Disparity Between Radar and Camera Features for Multi-modal Fusion 3D Object Detectioncited by 46
  18. 2024Co-Occ: Coupling Explicit Feature Fusion with Volume Rendering Regularization for Multi-Modal 3D Semantic Occupancy Predictioncited by 46
  19. 2023UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye Viewcited by 43
  20. 2024MonoOcc: Digging into Monocular Semantic Occupancy Predictioncited by 43
  21. 2023PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awarenesscited by 42
  22. 2023Camera-based 3D Semantic Scene Completion with Sparse Guidance Networkcited by 40
  23. 2021Semantic Segmentation-assisted Scene Completion for LiDAR Point Cloudscited by 37
  24. 2024OccFusion: Multi-Sensor Fusion Framework for 3D Semantic Occupancy Predictioncited by 32
  25. 2024RadarOcc: Robust 3D Occupancy Prediction with 4D Imaging Radarcited by 32
  26. 2023SSC-RS: Elevate LiDAR Semantic Scene Completion with Representation Separation and BEV Fusioncited by 30
  27. 2023X3KD: Knowledge Distillation Across Modalities, Tasks and Stages for Multi-Camera 3D Object Detectioncited by 28
  28. 2024RadarDistill: Boosting Radar-based Object Detection Performance via Knowledge Distillation from LiDAR Featurescited by 27
  29. 2024CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillationcited by 27
  30. 2023RCM-Fusion: Radar-Camera Multi-Level Fusion for 3D Object Detectioncited by 23
  31. 2024RIDERS: Radar-Infrared Depth Estimation for Robust Sensingcited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 11; 2026: 5.

18 papers.

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  1. 2025Doracamom: Joint 3D Detection and Occupancy Prediction with Multi-view 4D Radars and Cameras for Omnidirectional Perceptioncited by 21
  2. 2025GaussianFormer3D: Multi-Modal Gaussian-based Semantic Occupancy Prediction with 3D Deformable Attentioncited by 14
  3. 2025L2COcc: Lightweight Camera-Centric Semantic Scene Completion via Distillation of LiDAR Modelcited by 8
  4. 2025CogDDN: A Cognitive Demand-Driven Navigation with Decision Optimization and Dual-Process Thinkingcited by 7
  5. 2025OneOcc: Semantic Occupancy Prediction for Legged Robots with a Single Panoramic Cameracited by 6
  6. 2024TiGDistill-BEV: Multi-view BEV 3D Object Detection via Target Inner-Geometry Learning Distillationcited by 4
  7. 20254D mmWave Radar for Sensing Enhancement in Adverse Environments: Advances and Challengescited by 4
  8. 2025MetaOcc: Spatio-Temporal Fusion of Surround-View 4D Radar and Camera for 3D Occupancy Prediction with Dual Training Strategiescited by 3
  9. 20254D-ROLLS: 4D Radar Occupancy Learning via LiDAR Supervisioncited by 3
  10. 2024A Comprehensive Review of 3D Object Detection in Autonomous Driving: Technological Advances and Future Directionscited by 2
  11. 2025Out-of-Distribution Semantic Occupancy Predictioncited by 2
  12. 2025Easy3D-Labels: Supervising Semantic Occupancy Estimation with 3D Pseudo-Labels for Automotive Perceptioncited by 2
6 more
  1. 2026Panoramic Multimodal Semantic Occupancy Prediction for Quadruped Robotscited by 2
  2. 2025TACOcc:Target-Adaptive Cross-Modal Fusion with Volume Rendering for 3D Semantic Occupancycited by 0
  3. 2026On Learning Spatial Structure from Pre-Beamforming Per-Antenna Range-Doppler Radar Measurementscited by 0
  4. 2026Height-Guided Projection Reparameterization for Camera-LiDAR Occupancycited by 0
  5. 2026CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretrainingcited by 0
  6. 2026SSC-Priors: Exploring Semantic and Visibility Priors to Boost Lidar Semantic Scene Completioncited by 0