mlsanityData to 14 Oct 2026

Revisiting Multimodal Fusion for 3D Anomaly Detection from an Architectural Perspective

arXiv 2412.17297 ↗First posted 23 Dec 2024cs.CVcited by 12

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Abstract (arXiv)

Existing efforts to boost multimodal fusion of 3D anomaly detection (3D-AD) primarily concentrate on devising more effective multimodal fusion strategies. However, little attention was devoted to analyzing the role of multimodal fusion architecture (topology) design in contributing to 3D-AD. In this paper, we aim to bridge this gap and present a systematic study on the impact of multimodal fusion architecture design on 3D-AD. This work considers the multimodal fusion architecture design at the intra-module fusion level, i.e., independent modality-specific modules, involving early, middle or late multimodal features with specific fusion operations, and also at the inter-module fusion level, i.e., the strategies to fuse those modules. In both cases, we first derive insights through theoretically and experimentally exploring how architectural designs influence 3D-AD. Then, we extend SOTA neural architecture search (NAS) paradigm and propose 3D-ADNAS to simultaneously search across multimodal fusion strategies and modality-specific modules for the first time.Extensive experiments show that 3D-ADNAS obtains consistent improvements in 3D-AD across various model capacities in terms of accuracy, frame rate, and memory usage, and it exhibits great potential in dealing with few-shot 3D-AD tasks.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 33 of its 46 references that are in the map. First posted on arXiv 23 Dec 2024.

Builds on

33 of 46 references.

References · 33

  1. 2017Learning Transferable Architectures for Scalable Image Recognitioncited by 1,101
  2. 2021CutPaste: Self-Supervised Learning for Anomaly Detection and Localizationcited by 531
  3. 2021DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detectioncited by 514
  4. 2022Anomaly Detection via Reverse Distillation from One-Class Embeddingcited by 421
  5. 2019Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddingscited by 386
  6. 2020Sub-Image Anomaly Detection with Deep Pyramid Correspondencescited by 300
  7. 2022A Unified Model for Multi-class Anomaly Detectioncited by 268
  8. 2023Deep Industrial Image Anomaly Detection: A Surveycited by 148
  9. 2023Multimodal Industrial Anomaly Detection via Hybrid Fusioncited by 139
  10. 2021Fully Convolutional Cross-Scale-Flows for Image-based Defect Detectioncited by 117
  11. 2022Asymmetric Student-Teacher Networks for Industrial Anomaly Detectioncited by 117
  12. 2023AnomalyDiffusion: Few-Shot Anomaly Image Generation with Diffusion Modelcited by 111
21 more
  1. 2021Trusted Multi-View Classificationcited by 94
  2. 2022Back to the Feature: Classical 3D Features are (Almost) All You Need for 3D Anomaly Detectioncited by 93
  3. 2022DSR -- A dual subspace re-projection network for surface anomaly detectioncited by 90
  4. 2019MFAS: Multimodal Fusion Architecture Searchcited by 84
  5. 2023Complementary Pseudo Multimodal Feature for Point Cloud Anomaly Detectioncited by 75
  6. 2023PyramidFlow: High-Resolution Defect Contrastive Localization using Pyramid Normalizing Flowcited by 74
  7. 2023Few-Shot Defect Image Generation via Defect-Aware Feature Manipulationcited by 67
  8. 2023Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Networkcited by 67
  9. 2022Anomaly Detection in 3D Point Clouds using Deep Geometric Descriptorscited by 66
  10. 2023IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturingcited by 64
  11. 2024SoftPatch: Unsupervised Anomaly Detection with Noisy Datacited by 55
  12. 2024R3D-AD: Reconstruction via Diffusion for 3D Anomaly Detectioncited by 45
  13. 2023EasyNet: An Easy Network for 3D Industrial Anomaly Detectioncited by 43
  14. 2020Deep Multimodal Neural Architecture Searchcited by 34
  15. 2023Cheating Depth: Enhancing 3D Surface Anomaly Detection via Depth Simulationcited by 33
  16. 2021MUFASA: Multimodal Fusion Architecture Search for Electronic Health Recordscited by 30
  17. 2024M3DM-NR: RGB-3D Noisy-Resistant Industrial Anomaly Detection via Multimodal Denoisingcited by 24
  18. 2023Few Shot Part Segmentation Reveals Compositional Logic for Industrial Anomaly Detectioncited by 19
  19. 2024Self-supervised Feature Adaptation for 3D Industrial Anomaly Detectioncited by 16
  20. 2024PointCore: Efficient Unsupervised Point Cloud Anomaly Detector Using Local-Global Featurescited by 5
  21. 2023Multi-Scale Distillation for RGB-D Anomaly Detection on the PD-REAL Datasetcited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 7.

12 papers.

  1. 2025Taming Anomalies with Down-Up Sampling Networks: Group Center Preserving Reconstruction for 3D Anomaly Detectioncited by 11
  2. 2025Fence Theorem: Towards Dual-Objective Semantic-Structure Isolation in Preprocessing Phase for 3D Anomaly Detectioncited by 4
  3. 2026Towards an Incremental Unified Multimodal Anomaly Detection: Augmenting Multimodal Denoising From an Information Bottleneck Perspectivecited by 4
  4. 2026Hierarchical Point-Patch Fusion with Adaptive Patch Codebook for 3D Shape Anomaly Detectioncited by 3
  5. 2025A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospectscited by 2
  6. 2025Listening to the Unspoken: Exploring "365" Aspects of Multimodal Interview Performance Assessmentcited by 1
  7. 2026Cross-Modal Mapping and Dual-Branch Reconstruction for 2D-3D Multimodal Industrial Anomaly Detectioncited by 1
  8. 2026TDFNet: Tri-projection Deformable Fusion Network for Panoramic Salient Object Detectioncited by 1
  9. 2025Physic-HM: Restoring Physical Generative Logic in Multimodal Anomaly Detection via Hierarchical Modulationcited by 0
  10. 2026CMDS-AD: Cross-Modal Dual-Stream Decoupling for Few-Shot Anomaly Detectioncited by 0
  11. 2026MVFM-3DAD: Multi-view Flow Matching for 3D Anomaly Detection via Density Proxy Estimationcited by 0
  12. 2026MIRAGE: How Conversation State Shapes Historical Evidence Use in Multimodal Personal Agentscited by 0