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Zillow Applied Science Research

Zillow applied science teams are actively publishing their work. The areas of investigation include computer vision, document understanding, natural language processing (NLP), and recommendation systems. This webpage lists our publications, and where code is available, links are provided (with separate licenses).

Computer Vision

Datasets

Cruz, S., Hutchcroft, W., Li, Y., Khosravan, N., Boyadzhiev, I., & Kang, S. B. (2021). Zillow indoor dataset: Annotated floor plans with 360deg panoramas and 3d room layouts. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2133-2143). [Paper] [Supplementary Material] [Code]

Featured Publications

Lambert, J., Li, Y. Boyadzhiev, I., Wixson, L., Narayana, M., Hutchcroft, W., Hays, J., Dellaert, F., & Kang, S.B. (2022). SALVe: Semantic Alignment Verification for Floorplan Reconstruction from Sparse Panoramas. European Conference on Computer Vision (ECCV), October 2022 (to appear).

Hutchcroft, W., Li, Y., Boyadzhiev, I., Wan, Z., Wang, H., & Kang, S.B. (2022). CoVisPose: Co-Visibility Pose Transformer for Wide-Baseline Relative Pose Estimation in 360 Indoor Panoramas. European Conference on Computer Vision (ECCV), October 2022 (to appear).

Zhi, T., Chen, B., Boyadzhiev, I., Kang, S. B., Hebert, M., & Narasimhan, S. G. (2022). Semantically Supervised Appearance Decomposition for Virtual Staging from a Single Panorama. ACM TOG and SIGGRAPH, 2022 (to appear). [Paper] [Code]

Yin, Y., Hutchcroft, W., Khosravan, N., Boyadzhiev, I., Fu, Y., & Kang, S. B. (2022). Generating Topological Structure of Floorplans from Room Attributes. ACM International Conference on Multimedia Retrieval (ICMR), 2022. [Paper] [Code - Coming Soon]

Min, Z., Khosravan, N., Bessinger, Z., Narayana, M., Kang, S. B., Dunn, E., & Boyadzhiev, I. (2022). LASER: LAtent SpacE Rendering for 2D Visual Localization. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022. (Oral). [Paper] [Code]

Wang, H., Hutchcroft, W., Li, Y., Wan, Z., Boyadzhiev, I., Tian, Y., & Kang, S. B. (2022). PSMNet: Position-aware Stereo Merging Network for Room Layout Estimation. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022. [Paper] [Code - Coming Soon]

Eder, M., Moulon, P., & Guan, L. (2019, September). Pano popups: Indoor 3d reconstruction with a plane-aware network. In 2019 International Conference on 3D Vision (3DV) (pp. 76-84). IEEE. [Paper]

Zou, C., Colburn, A., Shan, Q., & Hoiem, D. (2018). Layoutnet: Reconstructing the 3d room layout from a single rgb image. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 2051-2059). [Paper] [Code]

Yan, H., Shan, Q., & Furukawa, Y. (2018). RIDI: Robust IMU double integration. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 621-636). [Paper] [Code]

Izadinia, H., Shan, Q., & Seitz, S. M. (2017). Im2cad. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 5134-5143) 2017. [Paper]

Technical Reports

Ikehata, S., Boyadzhiev, I., Shan, Q., & Furukawa, Y. (2016). Panoramic structure from motion via geometric relationship detection. arXiv preprint arXiv:1612.01256. [Report]

Blog Posts

How the Zillow Indoor Dataset Facilitates Better 3D tours and Advances the Science of Indoor Spaces

Using SageMaker for Machine Learning Model Deployment with Zillow Floor Plans

Zillow Floor Plan: Training Models to Detect Windows, Doors and Openings in Panoramas

Computing at the Edge: On Device Stitching with Zillow 3D Homes

My Internship at Zillow Group AI Part 1: Attribute Recognition in Real Estate Listings

Behind Zillow 3D Home - Backend Algorithms

Vision & Deep Learning Meetup at Zillow on March 13

Organizing Real Estate Photo Collections for Visual Browsing

What Makes a Photo Click: Selecting Hero Images with Deep Learning

Deploying Deep Learning at Trulia

Document Understanding/Natural Language Processing (NLP)

Featured Publication

Rahmani, A. R., Li, L., Vanover, B., Bertrand, C., & Rawat, S. (2022). Towards Semantic Search for Community Question Answering for Mortgage Officers. Knowledge Discovery and Data Mining (KDD) Workshop on Document Understanding 2021. [Paper] [Video]

Videos

Zillow: Near Real-Time Natural Language Processing (NLP) for Customer Interactions

How Zillow and Genesys are transforming customer conversations

Building Speech Analytics Using AWS AI Services

Recommendation Systems/Time Series

Featured Publications

Chakraborty, S., Shah, S., Soltani, K., Swigart, A., Yang, L., & Buckingham, K. (2020, December). Building an automated and self-aware anomaly detection system. In 2020 IEEE International Conference on Big Data (Big Data) (pp. 1465-1475). IEEE. [Paper] [Code]

Chau, H., Balaneshin, S., Liu, K., & Linda, O. (2020, December). Understanding the tradeoff between cost and quality of expert annotations for keyphrase extraction. In Proceedings of the 14th Linguistic Annotation Workshop (pp. 74-86). [Paper]

Chaudhari, H. A., Lin, S., & Linda, O. (2020). A General Framework for Fairness in Multistakeholder Recommendations. 3rd FAccTRec Workshop: Responsible Recommendation. Fourteenth ACM Conference on Recommender Systems. 2020. [Paper]

Klevak, E., Lin, S., Martin, A., Linda, O., & Ringger, E. (2020). Out-Of-Bag Anomaly Detection. The Third International TrueFact Workshop: Making a Credible Web for Tomorrow. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 2021 [Paper]

Ringger, E., Chang, A., Fagnan, D., Kamath, S., Linda, O., Liu, W., ... & Zeghmi, T. (2018). Finding Your Home: Large-Scale Recommendation in a Vibrant Marketplace. ComplexRec 2018, 13. [Paper]

Blog Posts

Improving Recommendation Quality by Tapping into Listing Text

Utilizing both Explicit & Implicit Signals to Power Home Recommendations

Predicting Sparse Down-Funnel Events in Home Shopping with Transfer and Multi-target Learning

Topic Modeling for Real Estate Listing Descriptions

Home Embeddings for Similar Home Recommendations

Helping Buyers Explore the Real Estate Market via Personalized Recommendation Diversity

#mlread: The Machine Learning Reading Group in Zillow AI

Visualizing Matrix Factorization Using Self-Organizing Maps

Personalized Location Preference for Home Recommendations

Introduction to Recommendations at Zillow

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