arXiv Machine Learning June 30, 2026 By Vignesh Ram Nithin Kappagantula, Shayan Hassantabar

Room Scene Discovery and Grouping in Unstructured Vacation Rental Image Collections

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arXiv:2507. 00263v2 Announce Type: replace-cross Abstract: The rapid growth of vacation rental (VR) platforms has led to an increasing volume of property images, often uploaded without structured categorization.

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arXiv AI

Sep 16

Multimodal Cultural Heritage Architectural Style Classification for Residential Buildings in the UAE Based on CLIP Embeddings and SVM

The paper presents a multimodal machine learning framework that classifies Emirati residential architectural styles by combining visual features from images and textual descriptions using OpenAI's CLIP model. The unified 512‑dimensional embeddings are reduced with UMAP, clustered with K‑Means, and then used to train an SVM classifier, achieving a 98% accuracy across eight style clusters. This approach outperforms previous studies and demonstrates the value of integrating visual and textual data for cultural heritage analysis.

By Ahmed Ammar Kubba, Manar Abu Talib, Iman Ibrahim, Qassim Nasir

rag multimodal

arXiv Computer Vision

Sep 18

Instance Segmentation and Fine-grained Classification for Urban Buildings with Adaptive Region Dividing and Spatially-Supervised Contrastive Learning

The paper introduces an adaptive region‑dividing strategy that projects a 3D point cloud onto a bird’s‑eye‑view plane to detect building regions, then back‑projects bounding boxes to create structure‑aligned training blocks for unified scene‑level evaluation. It also proposes a fine‑grained classification model using a point transformer classifier and a spatially‑supervised contrastive loss to improve inter‑class discriminability, addressing class imbalance with a weighted cross‑entropy. Experiments on UrbanBIS and STPLS3D datasets show the method outperforms state‑of‑the‑art approaches in both building instance segmentation and fine‑grained classification.

By Weiyuan Zhang, Qi Zhang, Hui Huang

llms computer-vision benchmarks

arXiv Computer Vision

Sep 17

PolyLayout: Multi-room Manhattan Layout Estimation

arXiv:2608.03323v2 Announce Type: replace Abstract: Estimating room layouts from multi-view imagery is a core task for indoor scene understanding. Existing methods are typically limited either by poo...

By Gustav Hanning, Shaohui Liu, R\'emi Pautrat, Marc Pollefeys, Kalle {\AA}str\"om, Viktor Larsson

benchmarks

arXiv Machine Learning

Aug 6

BIM-Native Tokenization for Constraint-Aware Room Layout Synthesis

arXiv:2512. 04832v3 Announce Type: replace-cross Abstract: We present a BIM-native tokenization for room-level layout synthesis in Building Information Modeling (BIM) scenes.

By Manuel Ladron de Guevara, Jinmo Rhee, Ardavan Bidgoli, Vaidas Razgaitis, Michael Bergin

llms rag nlp benchmarks

arXiv AI

Jul 2

Lost in the Tail: Addressing Geographic Imbalance in Urban Visual Place Recognition

arXiv:2607. 00090v1 Announce Type: cross Abstract: Urban-scale Visual Place Recognition (VPR) aims to identify the geographic location of a query image by matching it against a geo-tagged database.

By Zhiyao Shu, Jiacheng Yang, Yang Lu, Waishan Qiu, Chuan Li, Da Chen

benchmarks

arXiv Machine Learning

Sep 22

MMS-VPR: A Fine-Grained Multimodal Street-Level Visual Place Recognition Dataset and Evaluation Benchmark for Dense Pedestrian Environments

arXiv:2505.12254v3 Announce Type: replace-cross Abstract: Existing visual place recognition (VPR) datasets predominantly rely on vehicle-mounted imagery, offer limited multimodal diversity, and under...

By Yiwei Ou, Xiaobin Ren, Ronggui Sun, Guansong Gao, Kaiqi Zhao, Manfredo Manfredini

llms multimodal benchmarks