# Stubborn: A Strong Baseline for Indoor Object Navigation

arXiv: https://arxiv.org/abs/2203.07359 · HTML: https://mlsanity.com/paper/2203.07359/

## Key facts

- Cited by 32 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 31 references that are in the map.
- First posted on arXiv 14 Mar 2022.

## Builds on (most cited first, 23 of 23)

- [Mask R-CNN](https://mlsanity.com/paper/1703.06870/) (2017)
- [Rethinking Atrous Convolution for Semantic Image Segmentation](https://mlsanity.com/paper/1706.05587/) (2017)
- [Matterport3D: Learning from RGB-D Data in Indoor Environments](https://mlsanity.com/paper/1709.06158/) (2017)
- [Curiosity-driven Exploration by Self-supervised Prediction](https://mlsanity.com/paper/1705.05363/) (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)
- [CoAtNet: Marrying Convolution and Attention for All Data Sizes](https://mlsanity.com/paper/2106.04803/) (2021)
- [On Evaluation of Embodied Navigation Agents](https://mlsanity.com/paper/1807.06757/) (2018)
- [Object Goal Navigation using Goal-Oriented Semantic Exploration](https://mlsanity.com/paper/2007.00643/) (2020)
- [ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects](https://mlsanity.com/paper/2006.13171/) (2020)
- [Cognitive Mapping and Planning for Visual Navigation](https://mlsanity.com/paper/1702.03920/) (2017)
- [Simple but Effective: CLIP Embeddings for Embodied AI](https://mlsanity.com/paper/2111.09888/) (2021)
- [Deep Feature Flow for Video Recognition](https://mlsanity.com/paper/1611.07715/) (2016)
- [Visual Semantic Navigation using Scene Priors](https://mlsanity.com/paper/1810.06543/) (2018)
- [Learning Exploration Policies for Navigation](https://mlsanity.com/paper/1903.01959/) (2019)
- [Visual Representations for Semantic Target Driven Navigation](https://mlsanity.com/paper/1805.06066/) (2018)
- [Intel RealSense Stereoscopic Depth Cameras](https://mlsanity.com/paper/1705.05548/) (2017)
- [Semantic Video Segmentation by Gated Recurrent Flow Propagation](https://mlsanity.com/paper/1612.08871/) (2016)
- [Auxiliary Tasks and Exploration Enable ObjectNav](https://mlsanity.com/paper/2104.04112/) (2021)
- [RedNet: Residual Encoder-Decoder Network for indoor RGB-D Semantic Segmentation](https://mlsanity.com/paper/1806.01054/) (2018)
- [Efficient Semantic Video Segmentation with Per-frame Inference](https://mlsanity.com/paper/2002.11433/) (2020)
- [Temporal Memory Attention for Video Semantic Segmentation](https://mlsanity.com/paper/2102.08643/) (2021)
- [Learning Object-conditioned Exploration using Distributed Soft Actor Critic](https://mlsanity.com/paper/2007.14545/) (2020)

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

- [ProcTHOR: Large-Scale Embodied AI Using Procedural Generation](https://mlsanity.com/paper/2206.06994/) (2022)
- [VLFM: Vision-Language Frontier Maps for Zero-Shot Semantic Navigation](https://mlsanity.com/paper/2312.03275/) (2023)
- [ZSON: Zero-Shot Object-Goal Navigation using Multimodal Goal Embeddings](https://mlsanity.com/paper/2206.12403/) (2022)
- [ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments](https://mlsanity.com/paper/2304.03047/) (2023)
- [RoboEXP: Action-Conditioned Scene Graph via Interactive Exploration for Robotic Manipulation](https://mlsanity.com/paper/2402.15487/) (2024)
- [3D-Aware Object Goal Navigation via Simultaneous Exploration and Identification](https://mlsanity.com/paper/2212.00338/) (2022)
- [Learning Navigational Visual Representations with Semantic Map Supervision](https://mlsanity.com/paper/2307.12335/) (2023)
- [Vision-Language Models Provide Promptable Representations for Reinforcement Learning](https://mlsanity.com/paper/2402.02651/) (2024)
- [CogNav: Cognitive Process Modeling for Object Goal Navigation with LLMs](https://mlsanity.com/paper/2412.10439/) (2024)
- [UAV-ON: A Benchmark for Open-World Object Goal Navigation with Aerial Agents](https://mlsanity.com/paper/2508.00288/) (2025)
- [Learning Generalizable Feature Fields for Mobile Manipulation](https://mlsanity.com/paper/2403.07563/) (2024)
- [SPIN: Simultaneous Perception, Interaction and Navigation](https://mlsanity.com/paper/2405.07991/) (2024)
- [PEANUT: Predicting and Navigating to Unseen Targets](https://mlsanity.com/paper/2212.02497/) (2022)
- [Object Goal Navigation with Recursive Implicit Maps](https://mlsanity.com/paper/2308.05602/) (2023)
- [Tag Map: A Text-Based Map for Spatial Reasoning and Navigation with Large Language Models](https://mlsanity.com/paper/2409.15451/) (2024)
- [LaMPP: Language Models as Probabilistic Priors for Perception and Action](https://mlsanity.com/paper/2302.02801/) (2023)
- [MOPA: Modular Object Navigation with PointGoal Agents](https://mlsanity.com/paper/2304.03696/) (2023)
- [Personalized Instance-based Navigation Toward User-Specific Objects in Realistic Environments](https://mlsanity.com/paper/2410.18195/) (2024)
- [Perception Matters: Enhancing Embodied AI with Uncertainty-Aware Semantic Segmentation](https://mlsanity.com/paper/2408.02297/) (2024)
- [CuriousBot: Interactive Mobile Exploration via Actionable 3D Relational Object Graph](https://mlsanity.com/paper/2501.13338/) (2025)
- [Implicit Obstacle Map-driven Indoor Navigation Model for Robust Obstacle Avoidance](https://mlsanity.com/paper/2308.12845/) (2023)
- [Distilling LLM Prior to Flow Model for Generalizable Agent's Imagination in Object Goal Navigation](https://mlsanity.com/paper/2508.09423/) (2025)
- [Leveraging Large Language Model-based Room-Object Relationships Knowledge for Enhancing Multimodal-Input Object Goal Navigation](https://mlsanity.com/paper/2403.14163/) (2024)
- [Causality-Aware Transformer Networks for Robotic Navigation](https://mlsanity.com/paper/2409.02669/) (2024)
- [OpenObject-NAV: Open-Vocabulary Object-Oriented Navigation Based on Dynamic Carrier-Relationship Scene Graph](https://mlsanity.com/paper/2409.18743/) (2024)
- [LagMemo: Language 3D Gaussian Splatting Memory for Multi-modal Open-vocabulary Multi-goal Visual Navigation](https://mlsanity.com/paper/2510.24118/) (2025)
- [Diffusion as Reasoning: Enhancing Object Navigation via Diffusion Model Conditioned on LLM-based Object-Room Knowledge](https://mlsanity.com/paper/2410.21842/) (2024)
- [Efficient and Generalizable Environmental Understanding for Visual Navigation](https://mlsanity.com/paper/2506.15377/) (2025)
- [FOM-Nav: Frontier-Object Maps for Object Goal Navigation](https://mlsanity.com/paper/2512.01009/) (2025)
- [Hierarchical Semantic-Augmented Navigation: Optimal Transport and Graph-Driven Reasoning for Vision-Language Navigation](https://mlsanity.com/paper/2606.01565/) (2026)

## Abstract (arXiv)

We present a strong baseline that surpasses the performance of previously published methods on the Habitat Challenge task of navigating to a target object in indoor environments. Our method is motivated from primary failure modes of prior state-of-the-art: poor exploration, inaccurate object identification, and agent getting trapped due to imprecise map construction. We make three contributions to mitigate these issues: (i) First, we show that existing map-based methods fail to effectively use semantic clues for exploration. We present a semantic-agnostic exploration strategy (called Stubborn) without any learning that surprisingly outperforms prior work. (ii) We propose a strategy for integrating temporal information to improve object identification. (iii) Lastly, due to inaccurate depth observation the agent often gets trapped in small regions. We develop a multi-scale collision map for obstacle identification that mitigates this issue.