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Instance-Specific Image Goal Navigation: Training Embodied Agents to Find Object Instances
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We consider the problem of embodied visual navigation given an image-goal (ImageNav) where an agent is initialized in an unfamiliar environment and tasked with navigating to a location 'described' by an image. Unlike related navigation tasks, ImageNav does not have a standardized task definition which makes comparison across methods difficult. Further, existing formulations have two problematic properties; (1) image-goals are sampled from random locations which can lead to ambiguity (e.g., looking at walls), and (2) image-goals match the camera specification and embodiment of the agent; this rigidity is limiting when considering user-driven downstream applications. We present the Instance-specific ImageNav task (InstanceImageNav) to address these limitations. Specifically, the goal image is 'focused' on some particular object instance in the scene and is taken with camera parameters independent of the agent. We instantiate InstanceImageNav in the Habitat Simulator using scenes from the Habitat-Matterport3D dataset (HM3D) and release a standardized benchmark to measure community progress.
Forward citations
Cited by 15 Pith papers
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Where to Look: Can Foundation Models Reach a Target Viewpoint Through Active Exploration?
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POINav: Benchmarking and Enhancing Final-Meters Arrival in Real-World Vision-Language Navigation
POINav-Bench provides the first high-fidelity real-world benchmark for POI-goal VLN using 3DGS reconstructions of 126k m² with 163 POIs, supported by a Brain-Action framework and 70K real signage-entrance dataset.
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MCNav: Memory-Aware Dynamic Cognitive Map for Zero-shot Goal-oriented Navigation
MCNav builds a dynamic cognitive map with goal re-validation and missed-goal re-exploration to reach state-of-the-art results on instance-level zero-shot navigation in HM3D environments.
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AnyImageNav: Any-View Geometry for Precise Last-Meter Image-Goal Navigation
AnyImageNav uses a semantic-to-geometric cascade with 3D multi-view foundation models to recover precise 6-DoF poses from goal images, achieving 0.27m position error and state-of-the-art success rates on Gibson and HM...
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LangMap: A Human-Verified Benchmark for Hierarchical Open-Vocabulary Goal Navigation
LangMap is a human-verified navigation benchmark with 18K tasks spanning scene-, room-, region-, and instance-level goals in real-world 3D scans, covering 414 object categories.
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VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method
A new vision-only long-horizon aerial navigation benchmark (VoLN-UAV) and a baseline method (VoLN-MLLM) that achieve 7.4%/4.5%/1.8% success on unseen Easy/Normal/Hard episodes.
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Plug-and-Play Label Map Diffusion for Universal Goal-Oriented Navigation
PLMD applies a denoising diffusion model to predict labels for unknown map regions, allowing goal localization in unexplored environments by substituting completed labels into existing navigation pipelines.
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FSUNav: A Cerebrum-Cerebellum Architecture for Fast, Safe, and Universal Zero-Shot Goal-Oriented Navigation
FSUNav's dual brain-inspired modules achieve state-of-the-art zero-shot goal navigation across heterogeneous robots with improved speed, safety, and generalization.
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Learning to Localize Reference Trajectories in Image-Space for Visual Navigation
LoTIS localizes a reference RGB trajectory in the robot's current view, predicting image-space coordinates, visibility, and distance to provide robot-agnostic guidance for navigation.
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ImagineNav++: Prompting Vision-Language Models as Embodied Navigator through Scene Imagination
ImagineNav++ achieves SOTA mapless visual navigation by prompting VLMs to select imagined future views generated from a human-preference-distilled module and maintained via selective foveation memory.
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SplatSearch: Instance Image Goal Navigation for Mobile Robots using 3D Gaussian Splatting and Diffusion Models
SplatSearch combines sparse-view 3D Gaussian Splatting, multi-view diffusion inpainting, and semantic/visual frontier scoring to achieve viewpoint-invariant instance image-goal navigation in unknown environments.
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ObjectReact: Learning Object-Relative Control for Visual Navigation
A controller trained purely on object-relative costmaps beats image-goal navigation on alt-goal, shortcut, and reverse-route tasks, with nearly height-invariant performance and qualitative sim-to-real transfer.
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TANGO: Traversability-Aware Navigation with Local Metric Control for Topological Goals
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Flying to Image-Specified Objects: 3D Quadrotor Navigation via Cross-Graph Memory and Viewpoint Planning
Proposes a hierarchical navigation framework with viewpoint-aware action nodes, cross-graph memory, and learning-based policy for quadrotor InstanceImageNav, claiming improvements over baselines in simulation and real...
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