Structured Generative Models for Scene Understanding
International Journal of Computer Vision, 2025. [All Versions]. This position paper argues for the use of structured generative models (SGMs) for the understanding of static scenes. This requires the reconstruction of a 3D scene from an input image (or a set of multi-view…
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Configurable 3D Scene Synthesis and 2D Image Rendering with Per-pixel Ground Truth Using Stochastic Grammars link.springer.com
International Journal of Computer Vision, 2018. [All Versions]. [Preprint]. This work proposes a systematic learning-based approach to the generation of massive quantities of synthetic 3D scenes and arbitrary numbers of photorealistic 2D images thereof, with associated ground…
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3D dynamic scene graphs: Actionable spatial perception with places, objects, and humans arxiv.org
RSS'20, 2020. [All Versions]. This paper presents a unified representation for actionable spatial perception: 3D Dynamic Scene Graphs. Scene graphs are directed graphs where nodes represent entities in the scene (e.g. objects, walls, rooms), and edges represent relations (e.g…
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ShapeAssembly: learning to generate programs for 3D shape structure synthesis dl.acm.org
ACM Transactions on Graphics, 2020. [All Versions]. Manually authoring 3D shapes is difficult and time consuming; generative models of 3D shapes offer compelling alternatives. Procedural representations are one such possibility: they offer high-quality and editable results but…
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A generative vision model that trains with high data efficiency and breaks text-based CAPTCHAs science.org
Science, 2017. [All Versions]. [Preprint]. Learning from a few examples and generalizing to markedly different situations are capabilities of human visual intelligence that are yet to be matched by leading machine learning models. By drawing inspiration from systems…
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The Scene Language: Representing Scenes with Programs, Words, and Embeddings arxiv.org
CVPR'25, 2025. [All Versions]. [Project]. This paper introduces the Scene Language, a visual scene representation that concisely and precisely describes the structure, semantics, and identity of visual scenes. It represents a scene with three key components: a program that…
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Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling arxiv.org
3D-GANs for 3D model generation and fun 3D furniture arithmetics from embeddings (think like word2vec word arithmetics with 3D furniture representations).
AGI & CoCoSci › Papers > Domain Specific Language > Declarative DSL Applications: “International Journal of Computer Vision, 2025. [All Versions]. This position paper argues for the use of structured generative models (SGMs) for the understanding of static scenes. This requires the reconstruction of a 3D scene from an input image (or a set of multi-view…”