# Localizing Discriminative Visual Landmarks for Place Recognition

arXiv: https://arxiv.org/abs/1904.06635 · HTML: https://mlsanity.com/paper/1904.06635/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Apr 2019.

## Built on by (most cited first, 21 of 21)

- [Where is your place, Visual Place Recognition?](https://mlsanity.com/paper/2103.06443/) (2021)
- [PDC-Net+: Enhanced Probabilistic Dense Correspondence Network](https://mlsanity.com/paper/2109.13912/) (2021)
- [CricaVPR: Cross-image Correlation-aware Representation Learning for Visual Place Recognition](https://mlsanity.com/paper/2402.19231/) (2024)
- [Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition](https://mlsanity.com/paper/2402.14505/) (2024)
- [SFD2: Semantic-guided Feature Detection and Description](https://mlsanity.com/paper/2304.14845/) (2023)
- [Revisit Anything: Visual Place Recognition via Image Segment Retrieval](https://mlsanity.com/paper/2409.18049/) (2024)
- [STA-VPR: Spatio-temporal Alignment for Visual Place Recognition](https://mlsanity.com/paper/2103.13580/) (2021)
- [MultiRes-NetVLAD: Augmenting Place Recognition Training with Low-Resolution Imagery](https://mlsanity.com/paper/2202.09146/) (2022)
- [SelaVPR++: Towards Seamless Adaptation of Foundation Models for Efficient Place Recognition](https://mlsanity.com/paper/2502.16601/) (2025)
- [Learning Semantics for Visual Place Recognition through Multi-Scale Attention](https://mlsanity.com/paper/2201.09701/) (2022)
- [RTG-SLAM: Real-time 3D Reconstruction at Scale using Gaussian Splatting](https://mlsanity.com/paper/2404.19706/) (2024)
- [AANet: Aggregation and Alignment Network with Semi-hard Positive Sample Mining for Hierarchical Place Recognition](https://mlsanity.com/paper/2310.05184/) (2023)
- [Large-Scale Gaussian Splatting SLAM](https://mlsanity.com/paper/2505.09915/) (2025)
- [Towards Implicit Aggregation: Robust Image Representation for Place Recognition in the Transformer Era](https://mlsanity.com/paper/2511.06024/) (2025)
- [Co-visual pattern augmented generative transformer learning for automobile geo-localization](https://mlsanity.com/paper/2203.09135/) (2022)
- [Deep Homography Estimation for Visual Place Recognition](https://mlsanity.com/paper/2402.16086/) (2024)
- [Discriminative and Semantic Feature Selection for Place Recognition towards Dynamic Environments](https://mlsanity.com/paper/2103.10023/) (2021)
- [Why-So-Deep: Towards Boosting Previously Trained Models for Visual Place Recognition](https://mlsanity.com/paper/2201.03212/) (2022)
- [Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency](https://mlsanity.com/paper/2402.09237/) (2024)
- [Distillation Improves Visual Place Recognition for Low Quality Images](https://mlsanity.com/paper/2310.06906/) (2023)
- [PRAM: Place Recognition Anywhere Model for Efficient Visual Localization](https://mlsanity.com/paper/2404.07785/) (2024)

## Abstract (arXiv)

We address the problem of visual place recognition with perceptual changes. The fundamental problem of visual place recognition is generating robust image representations which are not only insensitive to environmental changes but also distinguishable to different places. Taking advantage of the feature extraction ability of Convolutional Neural Networks (CNNs), we further investigate how to localize discriminative visual landmarks that positively contribute to the similarity measurement, such as buildings and vegetations. In particular, a Landmark Localization Network (LLN) is designed to indicate which regions of an image are used for discrimination. Detailed experiments are conducted on open source datasets with varied appearance and viewpoint changes. The proposed approach achieves superior performance against state-of-the-art methods.