SceneScript: Reconstructing Scenes With An Autoregressive Structured Language Model
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Abstract (arXiv)
We introduce SceneScript, a method that directly produces full scene models as a sequence of structured language commands using an autoregressive, token-based approach. Our proposed scene representation is inspired by recent successes in transformers & LLMs, and departs from more traditional methods which commonly describe scenes as meshes, voxel grids, point clouds or radiance fields. Our method infers the set of structured language commands directly from encoded visual data using a scene language encoder-decoder architecture. To train SceneScript, we generate and release a large-scale synthetic dataset called Aria Synthetic Environments consisting of 100k high-quality in-door scenes, with photorealistic and ground-truth annotated renders of egocentric scene walkthroughs. Our method gives state-of-the art results in architectural layout estimation, and competitive results in 3D object detection. Lastly, we explore an advantage for SceneScript, which is the ability to readily adapt to new commands via simple additions to the structured language, which we illustrate for tasks such as coarse 3D object part reconstruction.
Key facts. Cited by 96 papers in the map (data through 14 Oct 2026). Builds on 35 of its 54 references that are in the map. First posted on arXiv 19 Mar 2024.
Builds on
35 of 54 references.
References · 35
- 2017Attention Is All You Needcited by 60,361
- 2015Deep Residual Learning for Image Recognitioncited by 52,096
- 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,117
- 2014Sequence to Sequence Learning with Neural Networkscited by 2,986
- 2015Fast R-CNNcited by 2,933
- 2019The Curious Case of Neural Text Degenerationcited by 2,916
- 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
- 2020Center-based 3D Object Detection and Trackingcited by 1,144
- 2019Deep Hough Voting for 3D Object Detection in Point Cloudscited by 648
- 2020Searching Efficient 3D Architectures with Sparse Point-Voxel Convolutioncited by 423
- 2021ABO: Dataset and Benchmarks for Real-World 3D Object Understandingcited by 366
- 2021Pix2seq: A Language Modeling Framework for Object Detectioncited by 349
23 more
- 2021An End-to-End Transformer Model for 3D Object Detectioncited by 329
- 2021DeepCAD: A Deep Generative Network for Computer-Aided Design Modelscited by 271
- 2020PolyGen: An Autoregressive Generative Model of 3D Meshescited by 269
- 2023Project Aria: A New Tool for Egocentric Multi-Modal AI Researchcited by 208
- 2022SoftGroup for 3D Instance Segmentation on Point Cloudscited by 200
- 2016Learning Shape Abstractions by Assembling Volumetric Primitivescited by 181
- 2022Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wildcited by 160
- 2020DeepSVG: A Hierarchical Generative Network for Vector Graphics Animationcited by 159
- 2021ImVoxelNet: Image to Voxels Projection for Monocular and Multi-View General-Purpose 3D Object Detectioncited by 157
- 2022SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebookscited by 125
- 2018PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Imagecited by 105
- 2018LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Imagecited by 95
- 2021Computer-Aided Design as Languagecited by 82
- 2022TorchSparse: Efficient Point Cloud Inference Enginecited by 73
- 2021SketchGen: Generating Constrained CAD Sketchescited by 68
- 2022Connecting the Dots: Floorplan Reconstruction Using Two-Level Queriescited by 49
- 2020SceneCAD: Predicting Object Alignments and Layouts in RGB-D Scanscited by 44
- 2021Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Cloudscited by 44
- 2017RoomNet: End-to-End Room Layout Estimationcited by 38
- 2019Floor-SP: Inverse CAD for Floorplans by Sequential Room-wise Shortest Pathcited by 36
- 2020PLAD: Learning to Infer Shape Programs with Pseudo-Labels and Approximate Distributionscited by 19
- 2022RayTran: 3D pose estimation and shape reconstruction of multiple objects from videos with ray-traced transformerscited by 17
- 2022Point2Seq: Detecting 3D Objects as Sequencescited by 15
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Citing papers per year: 2024: 10; 2025: 32; 2026: 54.
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- 2026Boosting MLLM Spatial Reasoning with Geometrically Referenced 3D Scene Representations9 Mar 2026
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- 2026FIRE3D: Feed-forward Interactive 3D Scene Reconstruction Within A Minute8 Sep 2026
- 2026Revisiting Local Context for Long-Horizon Streaming 3D Reconstruction27 Aug 2026
- 2026When Should a Network Emit Geometry, and When Should It Detect It? Readout, Reconciliation, and Representation in Floorplan Vectorization26 Aug 2026
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