mlsanityData to 14 Oct 2026

NeRF-Based defect detection

arXiv 2504.00270 ↗First posted 31 Mar 2025cs.CVcited by 7

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Abstract (arXiv)

The rapid growth of industrial automation has highlighted the need for precise and efficient defect detection in large-scale machinery. Traditional inspection techniques, involving manual procedures such as scaling tall structures for visual evaluation, are labor-intensive, subjective, and often hazardous. To overcome these challenges, this paper introduces an automated defect detection framework built on Neural Radiance Fields (NeRF) and the concept of digital twins. The system utilizes UAVs to capture images and reconstruct 3D models of machinery, producing both a standard reference model and a current-state model for comparison. Alignment of the models is achieved through the Iterative Closest Point (ICP) algorithm, enabling precise point cloud analysis to detect deviations that signify potential defects. By eliminating manual inspection, this method improves accuracy, enhances operational safety, and offers a scalable solution for defect detection. The proposed approach demonstrates great promise for reliable and efficient industrial applications.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 13 of its 23 references that are in the map. First posted on arXiv 31 Mar 2025.

Builds on

13 of 23 references.

References · 13

  1. 2018Contextual Hourglass Network for Semantic Segmentation of High Resolution Aerial Imagerycited by 43
  2. 2024A Comparative Study on Enhancing Prediction in Social Network Advertisement through Data Augmentationcited by 21
  3. 2024Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methodscited by 16
  4. 2024Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategiescited by 12
  5. 2024Deep Learning for Weather Forecasting: A CNN-LSTM Hybrid Model for Predicting Historical Temperature Datacited by 9
  6. 2024Self-Adaptive Robust Motion Planning for High DoF Robot Manipulator using Deep MPCcited by 8
  7. 2024Style Transfer: From Stitching to Neural Networkscited by 8
  8. 2024Comprehensive Overview of Artificial Intelligence Applications in Modern Industriescited by 6
  9. 2024Enhancing Diffusion-based Point Cloud Generation with Smoothness Constraintcited by 5
  10. 2024Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXtcited by 5
  11. 2024A Review of Electromagnetic Elimination Methods for low-field portable MRI scannercited by 4
  12. 2024Optimized Coordination Strategy for Multi-Aerospace Systems in Pick-and-Place Tasks By Deep Neural Networkcited by 3
1 more
  1. 2021V2F-Net: Explicit Decomposition of Occluded Pedestrian Detectioncited by 2

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Cited by year

Citing papers per year: 2025: 7.

7 papers.

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  3. 2025Evaluating Supervised Learning Models for Fraud Detection: A Comparative Study of Classical and Deep Architectures on Imbalanced Transaction Datacited by 20
  4. 2025Research on Personalized Financial Product Recommendation by Integrating Large Language Models and Graph Neural Networkscited by 6
  5. 2025Instruction Tuning and CoT Prompting for Contextual Medical QA with LLMscited by 5
  6. 2025A Machine Learning-Based Study on the Synergistic Optimization of Supply Chain Management and Financial Supply Chains from an Economic Perspectivecited by 1
  7. 2025Modality-Aware Infrared and Visible Image Fusion with Target-Aware Supervisioncited by 1