# Robust Visual Localization in Compute-Constrained Environments by Salient Edge Rendering and Weighted Hamming Similarity

arXiv: https://arxiv.org/abs/2509.25520 · HTML: https://mlsanity.com/paper/2509.25520/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 48 references that are in the map.
- First posted on arXiv 29 Sep 2025.

## Builds on (most cited first, 16 of 16)

- [Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer](https://mlsanity.com/paper/1907.01341/) (2019)
- [SuperGlue: Learning Feature Matching with Graph Neural Networks](https://mlsanity.com/paper/1911.11763/) (2019)
- [LoFTR: Detector-Free Local Feature Matching with Transformers](https://mlsanity.com/paper/2104.00680/) (2021)
- [PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation](https://mlsanity.com/paper/1812.11788/) (2018)
- [DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion](https://mlsanity.com/paper/1901.04780/) (2019)
- [Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation](https://mlsanity.com/paper/2312.02145/) (2023)
- [DeepIM: Deep Iterative Matching for 6D Pose Estimation](https://mlsanity.com/paper/1804.00175/) (2018)
- [Structured Pruning for Deep Convolutional Neural Networks: A survey](https://mlsanity.com/paper/2303.00566/) (2023)
- [SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose Estimation](https://mlsanity.com/paper/2311.15707/) (2023)
- [Diversity Matters: Fully Exploiting Depth Clues for Reliable Monocular 3D Object Detection](https://mlsanity.com/paper/2205.09373/) (2022)
- [Beyond Controlled Environments: 3D Camera Re-Localization in Changing Indoor Scenes](https://mlsanity.com/paper/2008.02004/) (2020)
- [Line-based 6-DoF Object Pose Estimation and Tracking With an Event Camera](https://mlsanity.com/paper/2408.03225/) (2024)
- [A Region-based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking](https://mlsanity.com/paper/1807.02087/) (2018)
- [Focal Length and Object Pose Estimation via Render and Compare](https://mlsanity.com/paper/2204.05145/) (2022)
- [Fusing Visual Appearance and Geometry for Multi-modality 6DoF Object Tracking](https://mlsanity.com/paper/2302.11458/) (2023)
- [Rover Relocalization for Mars Sample Return by Virtual Template Synthesis and Matching](https://mlsanity.com/paper/2103.03395/) (2021)

## Abstract (arXiv)

We consider the problem of vision-based 6-DoF object pose estimation in the context of the notional Mars Sample Return campaign, in which a robotic arm would need to localize multiple objects of interest for low-clearance pickup and insertion, under severely constrained hardware. We propose a novel localization algorithm leveraging a custom renderer together with a new template matching metric tailored to the edge domain to achieve robust pose estimation using only low-fidelity, textureless 3D models as inputs. Extensive evaluations on synthetic datasets as well as from physical testbeds on Earth and in situ Mars imagery shows that our method consistently beats the state of the art in compute and memory-constrained localization, both in terms of robustness and accuracy, in turn enabling new possibilities for cheap and reliable localization on general-purpose hardware.