mlsanityData to 7 Oct 2026

PIC-Net: Point Cloud and Image Collaboration Network for Large-Scale Place Recognition

arXiv 2008.00658 ↗First posted 3 Aug 2020cs.CVcited by 16

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Abstract (arXiv)

Place recognition is one of the hot research fields in automation technology and is still an open issue, Camera and Lidar are two mainstream sensors used in this task, Camera-based methods are easily affected by illumination and season changes, LIDAR cannot get the rich data as the image could , In this paper, we propose the PIC-Net (Point cloud and Image Collaboration Network), which use attention mechanism to fuse the features of image and point cloud, and mine the complementary information between the two. Furthermore, in order to improve the recognition performance at night, we transform the night image into the daytime style. Comparison results show that the collaboration of image and point cloud outperform both image-based and point cloud-based method, the attention strategy and day-night-transform could further improve the performance.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Aug 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 0; 2023: 4; 2024: 6; 2025: 0; 2026: 2.

16 papers.

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  1. 2021MinkLoc++: Lidar and Monocular Image Fusion for Place Recognitioncited by 41
  2. 2021AdaFusion: Visual-LiDAR Fusion with Adaptive Weights for Place Recognitioncited by 36
  3. 2023LCPR: A Multi-Scale Attention-Based LiDAR-Camera Fusion Network for Place Recognitioncited by 17
  4. 2021AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognitioncited by 10
  5. 2023DistilVPR: Cross-Modal Knowledge Distillation for Visual Place Recognitioncited by 8
  6. 2024MSSPlace: Multi-Sensor Place Recognition with Visual and Text Semanticscited by 7
  7. 2024GSPR: Multimodal Place Recognition Using 3D Gaussian Splatting for Autonomous Drivingcited by 7
  8. 2021Attention Models for Point Clouds in Deep Learning: A Surveycited by 6
  9. 2024MinkUNeXt: Point Cloud-based Large-scale Place Recognition using 3D Sparse Convolutionscited by 6
  10. 2024Explicit Interaction for Fusion-Based Place Recognitioncited by 4
  11. 2026VGGT-MPR: VGGT-Enhanced Multimodal Place Recognition in Autonomous Driving Environmentscited by 4
  12. 2024BEV2PR: BEV-Enhanced Visual Place Recognition with Structural Cuescited by 3
4 more
  1. 20233D objects and scenes classification, recognition, segmentation, and reconstruction using 3D point cloud data: A reviewcited by 2
  2. 2024PRFusion: Toward Effective and Robust Multi-Modal Place Recognition with Image and Point Cloud Fusioncited by 2
  3. 2023Camera-LiDAR Fusion with Latent Contact for Place Recognition in Challenging Cross-Scenescited by 1
  4. 2026MAG-VLAQ: Multi-modal Aerial-Ground Query Aggregation for Cross-View Place Recognitioncited by 0