# FGPrompt: Fine-grained Goal Prompting for Image-goal Navigation

arXiv: https://arxiv.org/abs/2310.07473 · HTML: https://mlsanity.com/paper/2310.07473/

## Key facts

- Cited by 22 papers in the map (data through 14 Oct 2026).
- Builds on 46 of its 52 references that are in the map.
- First posted on arXiv 11 Oct 2023.

## Builds on (most cited first, 30 of 46)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [FiLM: Visual Reasoning with a General Conditioning Layer](https://mlsanity.com/paper/1709.07871/) (2017)
- [RT-1: Robotics Transformer for Real-World Control at Scale](https://mlsanity.com/paper/2212.06817/) (2022)
- [SuperGlue: Learning Feature Matching with Graph Neural Networks](https://mlsanity.com/paper/1911.11763/) (2019)
- [Matterport3D: Learning from RGB-D Data in Indoor Environments](https://mlsanity.com/paper/1709.06158/) (2017)
- [SuperPoint: Self-Supervised Interest Point Detection and Description](https://mlsanity.com/paper/1712.07629/) (2017)
- [Habitat: A Platform for Embodied AI Research](https://mlsanity.com/paper/1904.01201/) (2019)
- [ORB-SLAM: a Versatile and Accurate Monocular SLAM System](https://mlsanity.com/paper/1502.00956/) (2015)
- [Habitat-Matterport 3D Dataset (HM3D): 1000 Large-scale 3D Environments for Embodied AI](https://mlsanity.com/paper/2109.08238/) (2021)
- [On Evaluation of Embodied Navigation Agents](https://mlsanity.com/paper/1807.06757/) (2018)
- [BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning](https://mlsanity.com/paper/2202.02005/) (2022)
- [Habitat 2.0: Training Home Assistants to Rearrange their Habitat](https://mlsanity.com/paper/2106.14405/) (2021)
- [Target-driven Visual Navigation in Indoor Scenes using Deep Reinforcement Learning](https://mlsanity.com/paper/1609.05143/) (2016)
- [Learning to Explore using Active Neural SLAM](https://mlsanity.com/paper/2004.05155/) (2020)
- [Cognitive Mapping and Planning for Visual Navigation](https://mlsanity.com/paper/1702.03920/) (2017)
- [Semi-parametric Topological Memory for Navigation](https://mlsanity.com/paper/1803.00653/) (2018)
- [Neural Topological SLAM for Visual Navigation](https://mlsanity.com/paper/2005.12256/) (2020)
- [Eigen-CAM: Class Activation Map using Principal Components](https://mlsanity.com/paper/2008.00299/) (2020)
- [ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings](https://mlsanity.com/paper/2206.12403/) (2022)
- [Open-World Object Manipulation using Pre-trained Vision-Language Models](https://mlsanity.com/paper/2303.00905/) (2023)
- [Habitat-Web: Learning Embodied Object-Search Strategies from Human Demonstrations at Scale](https://mlsanity.com/paper/2204.03514/) (2022)
- [Scene Memory Transformer for Embodied Agents in Long-Horizon Tasks](https://mlsanity.com/paper/1903.03878/) (2019)
- [Interpreting Deep Visual Representations via Network Dissection](https://mlsanity.com/paper/1711.05611/) (2017)
- [Visual Room Rearrangement](https://mlsanity.com/paper/2103.16544/) (2021)
- [Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation](https://mlsanity.com/paper/2210.07506/) (2022)
- [RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning](https://mlsanity.com/paper/2011.07949/) (2020)
- [Offline Visual Representation Learning for Embodied Navigation](https://mlsanity.com/paper/2204.13226/) (2022)
- [OVRL-V2: A simple state-of-art baseline for ImageNav and ObjectNav](https://mlsanity.com/paper/2303.07798/) (2023)
- [Zero Experience Required: Plug & Play Modular Transfer Learning for Semantic Visual Navigation](https://mlsanity.com/paper/2202.02440/) (2022)

## Built on by (most cited first, 22 of 22)

- [GaussNav: Gaussian Splatting for Visual Navigation](https://mlsanity.com/paper/2403.11625/) (2024)
- [LSceneLLM: Enhancing Large 3D Scene Understanding Using Adaptive Visual Preferences](https://mlsanity.com/paper/2412.01292/) (2024)
- [OctoNav: Towards Generalist Embodied Navigation](https://mlsanity.com/paper/2506.09839/) (2025)
- [Prioritized Semantic Learning for Zero-shot Instance Navigation](https://mlsanity.com/paper/2403.11650/) (2024)
- [REGNav: Room Expert Guided Image-Goal Navigation](https://mlsanity.com/paper/2502.10785/) (2025)
- [NavigateDiff: Visual Predictors are Zero-Shot Navigation Assistants](https://mlsanity.com/paper/2502.13894/) (2025)
- [SIGN: Safety-Aware Image-Goal Navigation for Autonomous Drones via Reinforcement Learning](https://mlsanity.com/paper/2508.12394/) (2025)
- [NOLO: Navigate Only Look Once](https://mlsanity.com/paper/2408.01384/) (2024)
- [Image-Goal Navigation Using Refined Feature Guidance and Scene Graph Enhancement](https://mlsanity.com/paper/2503.10986/) (2025)
- [Hierarchical Scoring with 3D Gaussian Splatting for Instance Image-Goal Navigation](https://mlsanity.com/paper/2506.07338/) (2025)
- [MG-Nav: Dual-Scale Visual Navigation via Sparse Spatial Memory](https://mlsanity.com/paper/2511.22609/) (2025)
- [RANa: Retrieval-Augmented Navigation](https://mlsanity.com/paper/2504.03524/) (2025)
- [What does really matter in image goal navigation?](https://mlsanity.com/paper/2507.01667/) (2025)
- [VLD: Visual Language Goal Distance for Reinforcement Learning Navigation](https://mlsanity.com/paper/2512.07976/) (2025)
- [LangMap: A Human-Verified Benchmark for Hierarchical Open-Vocabulary Goal Navigation](https://mlsanity.com/paper/2602.02220/) (2026)
- [Context-Nav: Context-Driven Exploration and Viewpoint-Aware 3D Spatial Reasoning for Instance Navigation](https://mlsanity.com/paper/2603.09506/) (2026)
- [SpaAct: Spatially-Activated Transition Learning with Curriculum Adaptation for Vision-Language Navigation](https://mlsanity.com/paper/2604.27620/) (2026)
- [CoNav: A Benchmark for Human-Centered Collaborative Navigation](https://mlsanity.com/paper/2406.02425/) (2024)
- [RSRNav: Reasoning Spatial Relationship for Image-Goal Navigation](https://mlsanity.com/paper/2504.17991/) (2025)
- [Synthetic vs. Real Training Data for Visual Navigation](https://mlsanity.com/paper/2509.11791/) (2025)
- [PIG-Nav: Key Insights for Pretrained Image Goal Navigation Models](https://mlsanity.com/paper/2507.17220/) (2025)
- [CoReLIN: Constraint-based Reasoning for Zero-shot Lifelong Interactive Navigation](https://mlsanity.com/paper/2602.20055/) (2026)

## Abstract (arXiv)

Learning to navigate to an image-specified goal is an important but challenging task for autonomous systems. The agent is required to reason the goal location from where a picture is shot. Existing methods try to solve this problem by learning a navigation policy, which captures semantic features of the goal image and observation image independently and lastly fuses them for predicting a sequence of navigation actions. However, these methods suffer from two major limitations. 1) They may miss detailed information in the goal image, and thus fail to reason the goal location. 2) More critically, it is hard to focus on the goal-relevant regions in the observation image, because they attempt to understand observation without goal conditioning. In this paper, we aim to overcome these limitations by designing a Fine-grained Goal Prompting (FGPrompt) method for image-goal navigation. In particular, we leverage fine-grained and high-resolution feature maps in the goal image as prompts to perform conditioned embedding, which preserves detailed information in the goal image and guides the observation encoder to pay attention to goal-relevant regions. Compared with existing methods on the image-goal navigation benchmark, our method brings significant performance improvement on 3 benchmark datasets (i.e., Gibson, MP3D, and HM3D). Especially on Gibson, we surpass the state-of-the-art success rate by 8% with only 1/50 model size. Project page: https://xinyusun.github.io/fgprompt-pages