mlsanityData to 14 Oct 2026

4DRC-OCC: Robust Semantic Occupancy Prediction Through Fusion of 4D Radar and Camera

arXiv 2603.07794 ↗First posted 8 Mar 2026cs.CVcited by 2

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Abstract (arXiv)

Autonomous driving requires robust perception across diverse environmental conditions, yet 3D semantic occupancy prediction remains challenging under adverse weather and lighting. In this work, we present the first study combining 4D radar and camera data for 3D semantic occupancy prediction. Our fusion leverages the complementary strengths of both modalities: 4D radar provides reliable range, velocity, and angle measurements in challenging conditions, while cameras contribute rich semantic and texture information. We further show that integrating depth cues from camera pixels enables lifting 2D images to 3D, improving scene reconstruction accuracy. Additionally, we introduce a fully automatically labeled dataset for training semantic occupancy models, substantially reducing reliance on costly manual annotation. Experiments demonstrate the robustness of 4D radar across diverse scenarios, highlighting its potential to advance autonomous vehicle perception.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 42 of its 55 references that are in the map. First posted on arXiv 8 Mar 2026.

Builds on

42 of 55 references.

References · 42

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30 more
  1. 2023Tri-Perspective View for Vision-Based 3D Semantic Occupancy Predictioncited by 409
  2. 2021MonoScene: Monocular 3D Semantic Scene Completioncited by 363
  3. 2023Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Drivingcited by 332
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  6. 2020Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completioncited by 223
  7. 2023OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perceptioncited by 221
  8. 2023FB-OCC: 3D Occupancy Prediction based on Forward-Backward View Transformationcited by 165
  9. 2022M2BEV: Multi-Camera Joint 3D Detection and Segmentation with Unified Birds-Eye View Representationcited by 156
  10. 2022Simple-BEV: What Really Matters for Multi-Sensor BEV Perception?cited by 128
  11. 2023PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentationcited by 115
  12. 2023FB-BEV: BEV Representation from Forward-Backward View Transformationscited by 98
  13. 2023COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Predictioncited by 96
  14. 2020A Deep Learning-based Radar and Camera Sensor Fusion Architecture for Object Detectioncited by 70
  15. 2022CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformercited by 67
  16. 2023Radar-Camera Fusion for Object Detection and Semantic Segmentation in Autonomous Driving: A Comprehensive Reviewcited by 58
  17. 2023LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusioncited by 58
  18. 2023SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radarcited by 49
  19. 2023OctreeOcc: Efficient and Multi-Granularity Occupancy Prediction Using Octree Queriescited by 48
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  29. 2023Multi-Scale Occ: 4th Place Solution for CVPR 2023 3D Occupancy Prediction Challengecited by 7
  30. 2023Offline Tracking with Object Permanencecited by 7

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 20264D Radar Perception Algorithms for Autonomous Driving: A Reviewcited by 0
  2. 2026RadarGSOcc: Doppler-Aware 3D Semantic Occupancy Prediction Using 4D Radar Tensor with Geometric-Semantic Feature Extractioncited by 0