# Convolutional Neural Network-based Place Recognition

arXiv: https://arxiv.org/abs/1411.1509 · HTML: https://mlsanity.com/paper/1411.1509/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Nov 2014.

## Built on by (most cited first, 30 of 32)

- [Where is your place, Visual Place Recognition?](https://mlsanity.com/paper/2103.06443/) (2021)
- [Visual Place Recognition: A Tutorial](https://mlsanity.com/paper/2303.03281/) (2023)
- [Generalized Contrastive Optimization of Siamese Networks for Place Recognition](https://mlsanity.com/paper/2103.06638/) (2021)
- [LCPR: A Multi-Scale Attention-Based LiDAR-Camera Fusion Network for Place Recognition](https://mlsanity.com/paper/2311.03198/) (2023)
- [Improving Visual Place Recognition Performance by Maximising Complementarity](https://mlsanity.com/paper/2102.08416/) (2021)
- [Deep Learning for Visual Localization and Mapping: A Survey](https://mlsanity.com/paper/2308.14039/) (2023)
- [An Efficient and Scalable Collection of Fly-inspired Voting Units for Visual Place Recognition in Changing Environments](https://mlsanity.com/paper/2109.10986/) (2021)
- [FE-Fusion-VPR: Attention-based Multi-Scale Network Architecture for Visual Place Recognition by Fusing Frames and Events](https://mlsanity.com/paper/2211.12244/) (2022)
- [VINGS-Mono: Visual-Inertial Gaussian Splatting Monocular SLAM in Large Scenes](https://mlsanity.com/paper/2501.08286/) (2025)
- [Learning Sequence Descriptor based on Spatio-Temporal Attention for Visual Place Recognition](https://mlsanity.com/paper/2305.11467/) (2023)
- [Co-visual pattern augmented generative transformer learning for automobile geo-localization](https://mlsanity.com/paper/2203.09135/) (2022)
- [Self-Supervised Learning for Place Representation Generalization across Appearance Changes](https://mlsanity.com/paper/2303.02370/) (2023)
- [Explicit Interaction for Fusion-Based Place Recognition](https://mlsanity.com/paper/2402.17264/) (2024)
- [Sequence-Based Filtering for Visual Route-Based Navigation: Analysing the Benefits, Trade-offs and Design Choices](https://mlsanity.com/paper/2103.01994/) (2021)
- [Improving Road Segmentation in Challenging Domains Using Similar Place Priors](https://mlsanity.com/paper/2205.14112/) (2022)
- [Dynamically Modulating Visual Place Recognition Sequence Length For Minimum Acceptable Performance Scenarios](https://mlsanity.com/paper/2407.00863/) (2024)
- [VLAD-BuFF: Burst-aware Fast Feature Aggregation for Visual Place Recognition](https://mlsanity.com/paper/2409.19293/) (2024)
- [CoPR: Towards Accurate Visual Localization With Continuous Place-descriptor Regression](https://mlsanity.com/paper/2304.07426/) (2023)
- [PRISM-TopoMap: Online Topological Mapping with Place Recognition and Scan Matching](https://mlsanity.com/paper/2404.01674/) (2024)
- [LVLM-empowered Multi-modal Representation Learning for Visual Place Recognition](https://mlsanity.com/paper/2407.06730/) (2024)
- [A Machine Learning Framework for Automatic Prediction of Human Semen Motility](https://mlsanity.com/paper/2109.08049/) (2021)
- [Bi-directional Loop Closure for Visual SLAM](https://mlsanity.com/paper/2204.01524/) (2022)
- [Data Efficient Visual Place Recognition Using Extremely JPEG-Compressed Images](https://mlsanity.com/paper/2209.08343/) (2022)
- [Data-Efficient Sequence-Based Visual Place Recognition with Highly Compressed JPEG Images](https://mlsanity.com/paper/2302.13314/) (2023)
- [Addressing the challenges of loop detection in agricultural environments](https://mlsanity.com/paper/2408.15761/) (2024)
- [Sequential Place Learning: Heuristic-Free High-Performance Long-Term Place Recognition](https://mlsanity.com/paper/2103.02074/) (2021)
- [A Benchmark Comparison of Visual Place Recognition Techniques for Resource-Constrained Embedded Platforms](https://mlsanity.com/paper/2109.11002/) (2021)
- [Deep Dense Local Feature Matching and Vehicle Removal for Indoor Visual Localization](https://mlsanity.com/paper/2205.12544/) (2022)
- [Supervised Fine-tuning Evaluation for Long-term Visual Place Recognition](https://mlsanity.com/paper/2211.07696/) (2022)
- [Regressing Transformers for Data-efficient Visual Place Recognition](https://mlsanity.com/paper/2401.16304/) (2024)

## Abstract (arXiv)

Recently Convolutional Neural Networks (CNNs) have been shown to achieve state-of-the-art performance on various classification tasks. In this paper, we present for the first time a place recognition technique based on CNN models, by combining the powerful features learnt by CNNs with a spatial and sequential filter. Applying the system to a 70 km benchmark place recognition dataset we achieve a 75% increase in recall at 100% precision, significantly outperforming all previous state of the art techniques. We also conduct a comprehensive performance comparison of the utility of features from all 21 layers for place recognition, both for the benchmark dataset and for a second dataset with more significant viewpoint changes.