mlsanityData to 7 Oct 2026

MVT: Multi-view Vision Transformer for 3D Object Recognition

arXiv 2110.13083 ↗First posted 25 Oct 2021cs.CVcited by 34

Not on the map. Why?

Abstract (arXiv)

Inspired by the great success achieved by CNN in image recognition, view-based methods applied CNNs to model the projected views for 3D object understanding and achieved excellent performance. Nevertheless, multi-view CNN models cannot model the communications between patches from different views, limiting its effectiveness in 3D object recognition. Inspired by the recent success gained by vision Transformer in image recognition, we propose a Multi-view Vision Transformer (MVT) for 3D object recognition. Since each patch feature in a Transformer block has a global reception field, it naturally achieves communications between patches from different views. Meanwhile, it takes much less inductive bias compared with its CNN counterparts. Considering both effectiveness and efficiency, we develop a global-local structure for our MVT. Our experiments on two public benchmarks, ModelNet40 and ModelNet10, demonstrate the competitive performance of our MVT.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). Builds on 24 of its 40 references that are in the map. First posted on arXiv 25 Oct 2021.

Builds on

24 of 40 references.

References · 24

  1. 2017Attention Is All You Needcited by 59,932
  2. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  3. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  4. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  5. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  6. 2016Layer Normalizationcited by 5,579
  7. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  8. 2020Training data-efficient image transformers & distillation through attentioncited by 4,560
  9. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  10. 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutionscited by 1,960
  11. 2021Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNetcited by 1,096
  12. 2021CvT: Introducing Convolutions to Vision Transformerscited by 946
12 more
  1. 2021Transformer in Transformercited by 632
  2. 2021Twins: Revisiting the Design of Spatial Attention in Vision Transformerscited by 565
  3. 2015Multi-view Convolutional Neural Networks for 3D Shape Recognitioncited by 564
  4. 2021Rethinking Spatial Dimensions of Vision Transformerscited by 361
  5. 2016Volumetric and Multi-View CNNs for Object Classification on 3D Datacited by 240
  6. 2018VV-Net: Voxel VAE Net with Group Convolutions for Point Cloud Segmentationcited by 64
  7. 2021Container: Context Aggregation Networkcited by 37
  8. 2016GIFT: A Real-time and Scalable 3D Shape Search Enginecited by 31
  9. 2019Dominant Set Clustering and Pooling for Multi-View 3D Object Recognitioncited by 25
  10. 2016Pairwise Decomposition of Image Sequences for Active Multi-View Recognitioncited by 15
  11. 2019LP-3DCNN: Unveiling Local Phase in 3D Convolutional Neural Networkscited by 14
  12. 20173D-A-Nets: 3D Deep Dense Descriptor for Volumetric Shapes with Adversarial Networkscited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 11; 2023: 5; 2024: 7; 2025: 6; 2026: 3.

34 papers.

Sort:

By area:

  1. 2022AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognitioncited by 714
  2. 2021A Survey of Visual Transformerscited by 117
  3. 2021Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Predictioncited by 57
  4. 2022How to Train Vision Transformer on Small-scale Datasets?cited by 34
  5. 2022Defending Backdoor Attacks on Vision Transformer via Patch Processingcited by 19
  6. 2022BOAT: Bilateral Local Attention Vision Transformercited by 12
  7. 2022Transformers Improve Breast Cancer Diagnosis from Unregistered Multi-View Mammogramscited by 11
  8. 2023Group Multi-View Transformer for 3D Shape Analysis with Spatial Encodingcited by 4
  9. 2025Uni3D-MoE: Scalable Multimodal 3D Scene Understanding via Mixture of Expertscited by 4
  10. 2022An Energy-Based Prior for Generative Saliencycited by 3
  11. 2023Dynamic Visual Prompt Tuning for Parameter Efficient Transfer Learningcited by 3
  12. 2023RBFormer: Improve Adversarial Robustness of Transformer by Robust Biascited by 3
22 more
  1. 2024Advancements in Point Cloud-Based 3D Defect Detection and Classification for Industrial Systems: A Comprehensive Surveycited by 3
  2. 2024PEVA-Net: Prompt-Enhanced View Aggregation Network for Zero/Few-Shot Multi-View 3D Shape Recognitioncited by 3
  3. 2022R2-MLP: Round-Roll MLP for Multi-View 3D Object Recognitioncited by 2
  4. 2024VSFormer: Mining Correlations in Flexible View Set for Multi-view 3D Shape Understandingcited by 2
  5. 2022Learning Sequential Contexts using Transformer for 3D Hand Pose Estimationcited by 1
  6. 2022Multi-View Active Fine-Grained Recognitioncited by 1
  7. 2022Degenerate Swin to Win: Plain Window-based Transformer without Sophisticated Operationscited by 1
  8. 2023ViewFormer: View Set Attention for Multi-view 3D Shape Understandingcited by 1
  9. 2024S^2Former-OR: Single-Stage Bi-Modal Transformer for Scene Graph Generation in ORcited by 1
  10. 2024Beyond Viewpoint: Robust 3D Object Recognition under Arbitrary Views through Joint Multi-Part Representationcited by 1
  11. 2025Proto-FG3D: Prototype-based Interpretable Fine-Grained 3D Shape Classificationcited by 1
  12. 2025NeuroVoxel-LM: Language-Aligned 3D Perception via Dynamic Voxelization and Meta-Embeddingcited by 1
  13. 2025Reg3D: Reconstructive Geometry Instruction Tuning for 3D Scene Understandingcited by 1
  14. 2025MvBody: Multi-View-Based Hybrid Transformer Using Optical 3D Body Scan for Explainable Cesarean Section Predictioncited by 1
  15. 2022Multiple View Performers for Shape Completioncited by 0
  16. 2023Self-accumulative Vision Transformer for Bone Age Assessment Using the Sauvegrain Methodcited by 0
  17. 2024Random Token Fusion for Multi-View Medical Diagnosiscited by 0
  18. 2024Hierarchical mutual distillation for multi-view fusion: Learning from all possible view combinationscited by 0
  19. 2025LM-MCVT: A Lightweight Multi-modal Multi-view Convolutional-Vision Transformer Approach for 3D Object Recognitioncited by 0
  20. 2026Bridging the Dimensionality Gap: A Taxonomy and Survey of 2D Vision Model Adaptation for 3D Analysiscited by 0
  21. 2026OTCHA: Optimal Transport-driven Confidence-aware Latent Hub Alignment for Multi-View Medical Image Classificationcited by 0
  22. 2026SmartMage: Dynamic Modality Orchestration for 3D Scene Understandingcited by 0