# GOO: A Dataset for Gaze Object Prediction in Retail Environments

arXiv: https://arxiv.org/abs/2105.10793 · HTML: https://mlsanity.com/paper/2105.10793/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 28 references that are in the map.
- First posted on arXiv 22 May 2021.

## Builds on (most cited first, 11 of 11)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [ImageNet Large Scale Visual Recognition Challenge](https://mlsanity.com/paper/1409.0575/) (2014)
- [Feature Pyramid Networks for Object Detection](https://mlsanity.com/paper/1612.03144/) (2016)
- [Rich feature hierarchies for accurate object detection and semantic segmentation](https://mlsanity.com/paper/1311.2524/) (2013)
- [Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting](https://mlsanity.com/paper/1506.04214/) (2015)
- [TurkerGaze: Crowdsourcing Saliency with Webcam based Eye Tracking](https://mlsanity.com/paper/1504.06755/) (2015)
- [Detecting Attended Visual Targets in Video](https://mlsanity.com/paper/2003.02501/) (2020)
- [Connecting Gaze, Scene, and Attention: Generalized Attention Estimation via Joint Modeling of Gaze and Scene Saliency](https://mlsanity.com/paper/1807.10437/) (2018)
- [CAT2000: A Large Scale Fixation Dataset for Boosting Saliency Research](https://mlsanity.com/paper/1505.03581/) (2015)
- [Believe It or Not, We Know What You Are Looking at!](https://mlsanity.com/paper/1907.02364/) (2019)

## Built on by (most cited first, 26 of 26)

- [Gaze-LLE: Gaze Target Estimation via Large-Scale Learned Encoders](https://mlsanity.com/paper/2412.09586/) (2024)
- [ChildPlay: A New Benchmark for Understanding Children's Gaze Behaviour](https://mlsanity.com/paper/2307.01630/) (2023)
- [Automatic Gaze Analysis: A Survey of Deep Learning based Approaches](https://mlsanity.com/paper/2108.05479/) (2021)
- [A Modular Multimodal Architecture for Gaze Target Prediction: Application to Privacy-Sensitive Settings](https://mlsanity.com/paper/2307.05158/) (2023)
- [Multimodal Across Domains Gaze Target Detection](https://mlsanity.com/paper/2208.10822/) (2022)
- [Patch-level Gaze Distribution Prediction for Gaze Following](https://mlsanity.com/paper/2211.11062/) (2022)
- [GaTector: A Unified Framework for Gaze Object Prediction](https://mlsanity.com/paper/2112.03549/) (2021)
- [An End-to-End Review of Gaze Estimation and its Interactive Applications on Handheld Mobile Devices](https://mlsanity.com/paper/2307.00122/) (2023)
- [A Review of Driver Gaze Estimation and Application in Gaze Behavior Understanding](https://mlsanity.com/paper/2307.01470/) (2023)
- [A Gaze-grounded Visual Question Answering Dataset for Clarifying Ambiguous Japanese Questions](https://mlsanity.com/paper/2403.17545/) (2024)
- [Joint Gaze-Location and Gaze-Object Detection](https://mlsanity.com/paper/2308.13857/) (2023)
- [TransGOP: Transformer-Based Gaze Object Prediction](https://mlsanity.com/paper/2402.13578/) (2024)
- [GazeHTA: End-to-end Gaze Target Detection with Head-Target Association](https://mlsanity.com/paper/2404.10718/) (2024)
- [HAZE-Net: High-Frequency Attentive Super-Resolved Gaze Estimation in Low-Resolution Face Images](https://mlsanity.com/paper/2209.10167/) (2022)
- [VL4Gaze: Unleashing Vision-Language Models for Gaze Following](https://mlsanity.com/paper/2512.20735/) (2025)
- [Leveraging Multi-Modal Saliency and Fusion for Gaze Target Detection](https://mlsanity.com/paper/2504.19271/) (2025)
- [Sharingan: A Transformer-based Architecture for Gaze Following](https://mlsanity.com/paper/2310.00816/) (2023)
- [GazeTarget360: Towards Gaze Target Estimation in 360-Degree for Robot Perception](https://mlsanity.com/paper/2507.00253/) (2025)
- [GaTector+: A Unified Head-free Framework for Gaze Object and Gaze Following Prediction](https://mlsanity.com/paper/2510.25301/) (2025)
- [GazeMoE: Perception of Gaze Target with Mixture-of-Experts](https://mlsanity.com/paper/2603.06256/) (2026)
- [Multi-scale Object-Aware Gaze Estimation via Geometric Reasoning](https://mlsanity.com/paper/2606.29334/) (2026)
- [PAGE: Towards Practical Human-level Gaze Target Estimation](https://mlsanity.com/paper/2607.04860/) (2026)
- [TextGaze: Prompting Gaze Target Estimation with Textual Scene Cues](https://mlsanity.com/paper/2607.10130/) (2026)
- [Open-Vocabulary Gaze Object Prediction: Benchmark and Method](https://mlsanity.com/paper/2607.18827/) (2026)
- [Gaze-Anchored Social Net: Decoding Implicit Relations via Joint Modeling](https://mlsanity.com/paper/2607.22847/) (2026)
- [Gaze Target Estimation Anywhere with Concepts](https://mlsanity.com/paper/2608.11367/) (2026)

## Abstract (arXiv)

One of the most fundamental and information-laden actions humans do is to look at objects. However, a survey of current works reveals that existing gaze-related datasets annotate only the pixel being looked at, and not the boundaries of a specific object of interest. This lack of object annotation presents an opportunity for further advancing gaze estimation research. To this end, we present a challenging new task called gaze object prediction, where the goal is to predict a bounding box for a person's gazed-at object. To train and evaluate gaze networks on this task, we present the Gaze On Objects (GOO) dataset. GOO is composed of a large set of synthetic images (GOO Synth) supplemented by a smaller subset of real images (GOO-Real) of people looking at objects in a retail environment. Our work establishes extensive baselines on GOO by re-implementing and evaluating selected state-of-the art models on the task of gaze following and domain adaptation. Code is available on github.