Search Results for author:
Found 9 papers, 7 papers with code
Structured Outdoor Architecture Reconstruction by Exploration and Classification
This paper presents an explore-and-classify framework for structured architectural reconstruction from an aerial image.
House-GAN++: Generative Adversarial Layout Refinement Network towards Intelligent Computational Agent for Professional Architects
This paper proposes a generative adversarial layout refinement network for automated floorplan generation.
House-GAN++: Generative Adversarial Layout Refinement Networks
This paper proposes a novel generative adversarial layout refinement network for automated floorplan generation.
House-GAN: Relational Generative Adversarial Networks for Graph-constrained House Layout Generation
This paper proposes a novel graph-constrained generative adversarial network, whose generator and discriminator are built upon relational architecture.
Vectorizing World Buildings: Planar Graph Reconstruction by Primitive Detection and Relationship Inference
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.
Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction
In our problem, nodes correspond to building edges in an image.
Structured Label Inference for Visual Understanding
In this paper, we exploit this rich structure for performing graph-based inference in label space for a number of tasks: multi-label image and video classification and action detection in untrimmed videos.
Hierarchical Label Inference for Video Classification
Videos are a rich source of high-dimensional structured data, with a wide range of interacting components at varying levels of granularity.
Learning Genomic Representations to Predict Clinical Outcomes in Cancer
Genomics are rapidly transforming medical practice and basic biomedical research, providing insights into disease mechanisms and improving therapeutic strategies, particularly in cancer.
