29 citations · 73 across the 8 of their papers we have counts for
8 papers
Structured Outdoor Architecture Reconstruction by Exploration and Classification
Fuyang Zhang, Xiang Xu, Nelson Nauata +1
This paper presents an explore-and-classify framework for structured architectural reconstruction from an aerial image. Starting from a potentially imperfect building reconstructio…
House-GAN++: Generative Adversarial Layout Refinement Networks
Nelson Nauata, Sepidehsadat Hosseini, Kai-Hung Chang +3
This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation. Our architecture is an integration of a graph-constrained relationa…
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation
Nelson Nauata, Kai-Hung Chang, Chin-Yi Cheng +2
This paper proposes a novel graph-constrained generative adversarial network, whose generator and discriminator are built upon relational architecture. The main idea is to encode t…
Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Inference
Nelson Nauata, Yasutaka Furukawa
This paper tackles a 2D architecture vectorization problem, whose task is to infer an outdoor building architecture as a 2D planar graph from a single RGB image. We provide a new b…
Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction
Fuyang Zhang, Nelson Nauata, Yasutaka Furukawa
This paper proposes a novel message passing neural (MPN) architecture Conv-MPN, which reconstructs an outdoor building as a planar graph from a single RGB image. Conv-MPN is specif…
Structured Label Inference for Visual Understanding
Nelson Nauata, Hexiang Hu, Guang-Tong Zhou +3
Visual data such as images and videos contain a rich source of structured semantic labels as well as a wide range of interacting components. Visual content could be assigned with f…
Hierarchical Label Inference for Video Classification
Nelson Nauata, Jonathan Smith, Greg Mori
Videos are a rich source of high-dimensional structured data, with a wide range of interacting components at varying levels of granularity. In order to improve understanding of unc…
Learning Genomic Representations to Predict Clinical Outcomes in Cancer
Safoora Yousefi, Congzheng Song, Nelson Nauata +1
Genomics are rapidly transforming medical practice and basic biomedical research, providing insights into disease mechanisms and improving therapeutic strategies, particularly in c…