Room Scene Discovery and Grouping in Unstructured Vacation Rental Image Collections
Vignesh Ram Nithin Kappagantula, Shayan Hassantabar

TL;DR
This paper presents a machine learning pipeline for discovering and grouping room scenes in unstructured vacation rental images, enabling better spatial understanding and bed type identification, with high efficiency and accuracy.
Contribution
The authors introduce a novel, low-latency, sample-efficient machine learning pipeline for room scene discovery, grouping, and bed type identification in vacation rental images, outperforming existing methods.
Findings
Strong performance in room grouping accuracy
Effective bed type identification from images
Outperforms contrastive learning and pretrained clustering methods
Abstract
The rapid growth of vacation rental (VR) platforms has led to an increasing volume of property images, often uploaded without structured categorization. This lack of organization poses significant challenges for travelers attempting to understand the spatial layout of a property, particularly when multiple rooms of the same type are present. To address this issue, we introduce an effective approach for solving the room scene discovery and grouping problem, as well as identifying bed types within each bedroom group. This grouping is valuable for travelers to comprehend the spatial organization, layout, and the sleeping configuration of the property. We propose a computationally efficient machine learning pipeline characterized by low latency and the ability to perform effectively with sample-efficient learning, making it well-suited for real-time and data-scarce environments. The…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMultimodal Machine Learning Applications · Advanced Image and Video Retrieval Techniques · Robotics and Sensor-Based Localization
