2 citations · 4 across the 10 of their papers we have counts for
8 papers · 1 filter
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…
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…
PromptLNet: Region-Adaptive Aesthetic Enhancement via Prompt Guidance in Low-Light Enhancement Net
Jun Yin, Yangfan He, Miao Zhang +4
Learning and improving large language models through human preference feedback has become a mainstream approach, but it has rarely been applied to the field of low-light image enha…
TSCnet: A Text-driven Semantic-level Controllable Framework for Customized Low-Light Image Enhancement
Miao Zhang, Jun Yin, Pengyu Zeng +3
Deep learning-based image enhancement methods show significant advantages in reducing noise and improving visibility in low-light conditions. These methods are typically based on o…
A Cascading Cooperative Multi-agent Framework for On-ramp Merging Control Integrating Large Language Models
Miao Zhang, Zhenlong Fang, Tianyi Wang +4
Traditional Reinforcement Learning (RL) suffers from replicating human-like behaviors, generalizing effectively in multi-agent scenarios, and overcoming inherent interpretability i…