1 citations · 2 across the 8 of their papers we have counts for
9 papers
PlanCraft: Sketch, Refine, and Furnish for Architect-Inspired Progressive 3D Residential Scene Generation
Pengyu Zeng, Yuqin Dai, Jun Yin +7
Two structural insights have been overlooked in automated residential floor plan generation. First, design is inherently progressive. Architects begin with rough strokes and refine…
GreenPlanner: Practical Floorplan Layout Generation via an Energy-Aware and Function-Feasible Generative Framework
Pengyu Zeng, Yuqin Dai, Jun Yin +7
Building design directly affects human well-being and carbon emissions, yet generating spatial-functional and energy-compliant floorplans remains manual, costly, and non-scalable.…
UrbanGraph: Physics-Informed Spatio-Temporal Dynamic Heterogeneous Graphs for Urban Microclimate Prediction
Weilin Xin, Chenyu Huang, Peilin Li +2
With rapid urbanization, predicting urban microclimates has become critical, as it affects building energy demand and public health risks. However, existing generative and homogene…
FloorPlan-DeepSeek (FPDS): A multimodal approach to floorplan generation using vector-based next room prediction
Jun Yin, Pengyu Zeng, Jing Zhong +4
In the architectural design process, floor plan generation is inherently progressive and iterative. However, existing generative models for floor plans are predominantly end-to-end…
Segment Any Architectural Facades (SAAF):An automatic segmentation model for building facades, walls and windows based on multimodal semantics guidance
Peilin Li, Jun Yin, Jing Zhong +3
In the context of the digital development of architecture, the automatic segmentation of walls and windows is a key step in improving the efficiency of building information models…
FloorplanMAE:A self-supervised framework for complete floorplan generation from partial inputs
Jun Yin, Jing Zhong, Pengyu Zeng +4
In the architectural design process, floorplan design is often a dynamic and iterative process. Architects progressively draw various parts of the floorplan according to their idea…
ArchiLense: A Framework for Quantitative Analysis of Architectural Styles Based on Vision Large Language Models
Jing Zhong, Jun Yin, Peilin Li +4
Architectural cultures across regions are characterized by stylistic diversity, shaped by historical, social, and technological contexts in addition to geograph-ical conditions. Un…
ArchShapeNet:An Interpretable 3D-CNN Framework for Evaluating Architectural Shapes
Jun Yin, Jing Zhong, Pengyu Zeng +4
In contemporary architectural design, the growing complexity and diversity of design demands have made generative plugin tools essential for quickly producing initial concepts and…
UrbanSense:A Framework for Quantitative Analysis of Urban Streetscapes leveraging Vision Large Language Models
Jun Yin, Jing Zhong, Peilin Li +4
Urban cultures and architectural styles vary significantly across cities due to geographical, chronological, historical, and socio-political factors. Understanding these difference…