# EAGLE: Episodic Appearance- and Geometry-aware Memory for Unified 2D-3D Visual Query Localization in Egocentric Vision

arXiv: https://arxiv.org/abs/2511.08007 · HTML: https://mlsanity.com/paper/2511.08007/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 35 references that are in the map.
- First posted on arXiv 11 Nov 2025.

## Builds on (most cited first, 24 of 24)

- [DINOv2: Learning Robust Visual Features without Supervision](https://mlsanity.com/paper/2304.07193/) (2023)
- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [DUSt3R: Geometric 3D Vision Made Easy](https://mlsanity.com/paper/2312.14132/) (2023)
- [Learning Discriminative Model Prediction for Tracking](https://mlsanity.com/paper/1904.07220/) (2019)
- [ATOM: Accurate Tracking by Overlap Maximization](https://mlsanity.com/paper/1811.07628/) (2018)
- [Meta R-CNN : Towards General Solver for Instance-level Few-shot Learning](https://mlsanity.com/paper/1909.13032/) (2019)
- [EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations](https://mlsanity.com/paper/2209.13064/) (2022)
- [Know Your Surroundings: Exploiting Scene Information for Object Tracking](https://mlsanity.com/paper/2003.11014/) (2020)
- [High-Performance Long-Term Tracking with Meta-Updater](https://mlsanity.com/paper/2004.00305/) (2020)
- [D3S -- A Discriminative Single Shot Segmentation Tracker](https://mlsanity.com/paper/1911.08862/) (2019)
- [NeuralDiff: Segmenting 3D objects that move in egocentric videos](https://mlsanity.com/paper/2110.09936/) (2021)
- [Meta-Tracker: Fast and Robust Online Adaptation for Visual Object Trackers](https://mlsanity.com/paper/1801.03049/) (2018)
- [EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset](https://mlsanity.com/paper/2301.03213/) (2023)
- [EgoLoc: Revisiting 3D Object Localization from Egocentric Videos with Visual Queries](https://mlsanity.com/paper/2212.06969/) (2022)
- [Where is my Wallet? Modeling Object Proposal Sets for Egocentric Visual Query Localization](https://mlsanity.com/paper/2211.10528/) (2022)
- [Single-Stage Visual Query Localization in Egocentric Videos](https://mlsanity.com/paper/2306.09324/) (2023)
- [Instance Tracking in 3D Scenes from Egocentric Videos](https://mlsanity.com/paper/2312.04117/) (2023)
- [RELOCATE: A Simple Training-Free Baseline for Visual Query Localization Using Region-Based Representations](https://mlsanity.com/paper/2412.01826/) (2024)
- [PRVQL: Progressive Knowledge-guided Refinement for Robust Egocentric Visual Query Localization](https://mlsanity.com/paper/2502.07707/) (2025)
- [Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videos](https://mlsanity.com/paper/2101.02196/) (2021)
- [Ego3DT: Tracking Every 3D Object in Ego-centric Videos](https://mlsanity.com/paper/2410.08530/) (2024)
- [EgoCOL: Egocentric Camera pose estimation for Open-world 3D object Localization @Ego4D challenge 2023](https://mlsanity.com/paper/2306.16606/) (2023)
- [HERO-VQL: Hierarchical, Egocentric and Robust Visual Query Localization](https://mlsanity.com/paper/2509.00385/) (2025)
- [Hybrid Structure-from-Motion and Camera Relocalization for Enhanced Egocentric Localization](https://mlsanity.com/paper/2407.08023/) (2024)

## Built on by (most cited first, 3 of 3)

- [AI Smart Glasses for Wearable Intelligence: From Egocentric Sensing to Agentic Personalization](https://mlsanity.com/paper/2609.19793/) (2026)
- [Never Look Back: Understanding Persistence in 3D Object Memory from Egocentric Videos](https://mlsanity.com/paper/2610.10538/) (2026)
- [Remember, Revisit, Revise: Scaffold Memory for Long-Horizon 3D Geometry](https://mlsanity.com/paper/2610.19674/) (2026)

## Abstract (arXiv)

Egocentric visual query localization is vital for embodied AI and VR/AR, yet remains challenging due to camera motion, viewpoint changes, and appearance variations. We present EAGLE, a novel framework that leverages episodic appearance- and geometry-aware memory to achieve unified 2D-3D visual query localization in egocentric vision. Inspired by avian memory consolidation, EAGLE synergistically integrates segmentation guided by an appearance-aware meta-learning memory (AMM), with tracking driven by a geometry-aware localization memory (GLM). This memory consolidation mechanism, through structured appearance and geometry memory banks, stores high-confidence retrieval samples, effectively supporting both long- and short-term modeling of target appearance variations. This enables precise contour delineation with robust spatial discrimination, leading to significantly improved retrieval accuracy. Furthermore, by integrating the VQL-2D output with a visual geometry grounded Transformer (VGGT), we achieve a efficient unification of 2D and 3D tasks, enabling rapid and accurate back-projection into 3D space. Our method achieves state-ofthe-art performance on the Ego4D-VQ benchmark.