arXiv AI
Aug 11
Learning an Interior Layout Policy in a Domain Specific Language Action Space
arXiv:2608. 07547v1 Announce Type: cross Abstract: Indoor scene layout generation is a challenging task in interior design.
GFLAN: Generative Functional Layouts
arXiv:2512. 16275v2 Announce Type: replace-cross Abstract: Automated floor plan generation lies at the intersection of combinatorial search, geometric constraint satisfaction, and functional design requirements -- a confluence that has historically resisted a unified computational treatment.
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arXiv AI
Jun 10
Architect-Ant: Editable Automatic Furnishing of Architectural Floor Plans
arXiv:2606. 10953v1 Announce Type: new Abstract: Furnished floor plans are fundamental to real estate visualization, interior design, and architectural workflows.
arXiv AI
Jul 21
Think, Plan, Paint: Layout-Aware Reasoning for Controllable Image Generation in Unified Models
arXiv:2607. 16409v1 Announce Type: cross Abstract: Unified Multimodal Large Language Models (MLLMs) offer a promising paradigm for unifying visual understanding and generation, yet they still struggle to follow complex spatial instructions and logical constraints in controllable image generation.
arXiv AI
Jun 6
HomeWorld: A Unified Floorplan-to-Furnished Framework for Generating Controllable, Densely Interactive Whole-Home Scenes
arXiv:2606. 06390v1 Announce Type: cross Abstract: Indoor scene generation is crucial for robot simulation and modern interior design.
arXiv AI
Jun 16
SceneConductor: 3D Scene Generation from a Single Image with Multi-Agent Orchestration
arXiv:2606. 08402v2 Announce Type: replace-cross Abstract: Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context from inherently ambiguous visual evidence.
arXiv AI
Jun 9
SceneConductor: 3D Scene Generation from Single Image with Multi-Agent Orchestration
arXiv:2606. 08402v1 Announce Type: cross Abstract: Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context from inherently ambiguous visual evidence.
Hugging Face Trending Papers
Jul 15
ThinkBLOX: 3D Indoor Scene Generation with Progressive Reasoning
While traditional graphics methods often synthesize 3D indoor scenes autoregressively or hierarchically, recent vision-language model (VLM)-based generators predominantly adopt a one-shot paradigm where the full layout is planned at once. This one-shot approach often requires global re-optimization or complete reconstruction during interactive editing (e.
arXiv AI
Jun 10
Non-Parametric Structural Priors for Geometry Theorem Prediction
arXiv:2603. 04852v2 Announce Type: replace Abstract: Multi-step theorem prediction is a central challenge in geometry problem solving.
Hugging Face Trending Papers
Aug 6
Prior-SG: Task and Prior Driven Region Segmentation for Scene Graphs in Arbitrarily-Structured Environments
Hierarchical 3D scene graphs are a promising representation for high-level spatial reasoning in autonomous mobile platforms. However, existing extraction frameworks typically rely on purely local visual clustering or strict geometric heuristics, such as wall-separated rooms, which fail in open-plan or arbitrarily-structured environments.
arXiv Machine Learning
Jun 10
Geometry-Aware Reinforcement Learning for 2D Irregular Nesting
arXiv:2606. 10611v1 Announce Type: new Abstract: Traditional heuristic solvers for the 2D irregular nesting problem share a fundamental limitation: they are blind to polygon geometry, relying on guided brute-force to navigate the continuous placement space with minimal geometrical guidance.
arXiv AI
Jul 1
Motion Planning in Compressed Representation Spaces
arXiv:2606. 30940v1 Announce Type: cross Abstract: Deep learning methods have vastly expanded the capabilities of motion planning in robotics applications, as learning priors from large-scale data has been shown to be essential in capturing the highly complex behavior required for solving tasks such as manipulation or navigation for autonomous vehicles.
Hugging Face Trending Papers
Jun 9
Geometry-Aware Reinforcement Learning for 2D Irregular Nesting
Traditional heuristic solvers for the 2D irregular nesting problem share a fundamental limitation: they are blind to polygon geometry, relying on guided brute-force to navigate the continuous placement space with minimal geometrical guidance. In this paper, we argue that Reinforcement Learning is uniquely positioned to overcome this bottleneck.