most citedTSCnet: A Text-driven Semantic-level Controllable Framework for Customized Low-Light Image Enhancement

2 citations · 4 across the 13 of their papers we have counts for

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cs.CV2026

CrossProjection: Geometric Grounding Beyond Viewpoint Change in Architectural Drawings

Kaho Li, Pengyu Zeng, Yuqin Dai +3

Architectural drawings violate the usual assumption behind multi-view reasoning: plans and sections are cuts, while elevations are facade projections, so corresponding components c…

cs.CV2026

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…

cs.CV2026

Power Reinforcement Post-Training of Text-to-Image Models with Super-Linear Advantage Shaping

Haoyuan Sun, Jing Wang, Yuxin Song +9

Recently, post-training methods based on reinforcement learning, with a particular focus on Group Relative Policy Optimization (GRPO), have emerged as the robust paradigm for furth…

cs.CV2025★ 1 cited

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025★ 1 cited

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…

cs.CV2025

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…

cs.CV2025★ 2 cited

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…