Related papers: Integrating Floor Plans into Hedonic Models for Re…

In recent years several complaints about racial discrimination in appraising home values have been accumulating. For several decades, to estimate the sale price of the residential properties, appraisers have been walking through the…

Accurate prediction of house price, a vital aspect of the residential real estate sector, is of substantial interest for a wide range of stakeholders. However, predicting house prices is a complex task due to the significant variability…

When an individual purchases a home, they simultaneously purchase its structural features, its accessibility to work, and the neighborhood amenities. Some amenities, such as air quality, are measurable while others, such as the prestige or…

This study presents a new user experience in apartment searches using functionality and comfort as query items. This study has three technical contributions. First, we present a new dataset on the perceived functionality and comfort scores…

We study how deep learning can improve valuation in the art market by incorporating the visual content of artworks into predictive models. Using a large repeated-sales dataset from major auction houses, we benchmark classical hedonic…

The real estate market is exposed to many fluctuations in prices because of existing correlations with many variables, some of which cannot be controlled or might even be unknown. Housing prices can increase rapidly (or in some cases, also…

Real estate appraisal is a complex and important task, that can be made more precise and faster with the help of automated valuation tools. Usually the value of some property is determined by taking into account both structural and…

The ability to recognize the position and order of the floor-level lines that divide adjacent building floors can benefit many applications, for example, urban augmented reality (AR). This work tackles the problem of locating floor-level…

Real estate appraisal, which is the process of estimating the price for real estate properties, is crucial for both buys and sellers as the basis for negotiation and transaction. Traditionally, the repeat sales model has been widely adopted…

This paper details an innovative methodology to integrate image data into traditional econometric models. Motivated by forecasting sales prices for residential real estate, we harness the power of deep learning to add "information"…

The task of room layout estimation is to locate the wall-floor, wall-ceiling, and wall-wall boundaries. Most recent methods solve this problem based on edge/keypoint detection or semantic segmentation. However, these approaches have shown…

Predicting the price of a house remains a challenging issue that needs to be addressed. Research has attempted to establish a model with different methods and algorithms to predict the housing price, from the traditional hedonic model to a…

Real estate contributes significantly to all major economies around the world. In particular, house prices have a direct impact on stakeholders, ranging from house buyers to financing companies. Thus, a plethora of techniques have been…

Recognition of floor plans has been a challenging and popular task. Despite that many recent approaches have been proposed for this task, they typically fail to make the room-level unified prediction. Specifically, multiple semantic…

This paper presents a new approach to recognize elements in floor plan layouts. Besides walls and rooms, we aim to recognize diverse floor plan elements, such as doors, windows and different types of rooms, in the floor layouts. To this…

In this paper, we show how using publicly available data streams and machine learning algorithms one can develop practical data driven services with no input from domain experts as a form of prior knowledge. We report the initial steps…

Since the advent of online real estate database companies like Zillow, Trulia and Redfin, the problem of automatic estimation of market values for houses has received considerable attention. Several real estate websites provide such…

This dissertation uses supervised and unsupervised data mining techniques to analyse office floor plans in an attempt to gain a better understanding of their geometry-to-function relationship. This question was deemed relevant after a…

Floorplans provide a compact representation of the building's structure, revealing not only layout information but also detailed semantics such as the locations of windows and doors. However, contemporary floorplan localization techniques…

The use of Artificial Intelligence (AI) in the real estate market has been growing in recent years. In this paper, we propose a new method for property valuation that utilizes self-supervised vision transformers, a recent breakthrough in…