SceneCode compiles natural language prompts into executable code programs that generate editable, articulated indoor scenes for physics simulation.
Procthor: Large-scale embodied ai using procedural generation.Advances in Neural Information Processing Systems, 35:5982–5994
6 Pith papers cite this work. Polarity classification is still indexing.
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Introduces the first passive source attribution benchmark for 22 generative 3D models and a Transformer achieving 97.22% accuracy under full supervision and 77.17% with 1% training data.
A feed-forward feature-Gaussian plus one-step geometry-aware pixel-flow simulator converts large image collections into 20K interactive scenes and 10M+ navigation samples that improve zero-shot Habitat and real-robot performance.
Code-as-Room is an MLLM-based agentic pipeline that parses top-down images into multi-stage Blender code synthesis with cross-stage memory to generate functional 3D rooms.
SafeVLA applies constrained reinforcement learning via CMDP min-max optimization to VLAs, cutting safety violation costs by 83.58% while preserving task success on long-horizon mobile manipulation tasks.
citing papers explorer
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SceneCode: Executable World Programs for Editable Indoor Scenes with Articulated Objects
SceneCode compiles natural language prompts into executable code programs that generate editable, articulated indoor scenes for physics simulation.
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Who Generated This 3D Asset? Learning Source Attribution for Generative 3D Models
Introduces the first passive source attribution benchmark for 22 generative 3D models and a Transformer achieving 97.22% accuracy under full supervision and 77.17% with 1% training data.
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Image2Sim: Scaling Embodied Navigation via Generative Neural Simulator
A feed-forward feature-Gaussian plus one-step geometry-aware pixel-flow simulator converts large image collections into 20K interactive scenes and 10M+ navigation samples that improve zero-shot Habitat and real-robot performance.
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Code-as-Room: Generating 3D Rooms from Top-Down View Images via Agentic Code Synthesis
Code-as-Room is an MLLM-based agentic pipeline that parses top-down images into multi-stage Blender code synthesis with cross-stage memory to generate functional 3D rooms.
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SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learning
SafeVLA applies constrained reinforcement learning via CMDP min-max optimization to VLAs, cutting safety violation costs by 83.58% while preserving task success on long-horizon mobile manipulation tasks.
- ChronoAgentic: A Code-based Multi-Agent World Simulator for Physically Grounded Simulation Construction