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SemLayoutDiff: Semantic Layout Generation with Diffusion Model for Indoor Scene Synthesis
Xiaohao Sun, Divyam Goel, Angel X. Chang
We present SemLayoutDiff, a unified model for synthesizing diverse 3D indoor scenes across multiple room types. The model introduces a scene layout representation combining a top-d…
Hyperbolic Multimodal Representation Learning for Biological Taxonomies
ZeMing Gong, Chuanqi Tang, Xiaoliang Huo +6
Taxonomic classification in biodiversity research involves organizing biological specimens into structured hierarchies based on evidence, which can come from multiple modalities su…
MLFM: Multi-Layered Feature Maps for Richer Language Understanding in Zero-Shot Semantic Navigation
Sonia Raychaudhuri, Enrico Cancelli, Tommaso Campari +3
Recent progress in large vision-language models has driven improvements in language-based semantic navigation, where an embodied agent must reach a target object described in natur…
HSM: Hierarchical Scene Motifs for Multi-Scale Indoor Scene Generation
Hou In Derek Pun, Hou In Ivan Tam, Austin T. Wang +3
Despite advances in indoor 3D scene layout generation, synthesizing scenes with dense object arrangements remains challenging. Existing methods focus on large furniture while negle…
NuiScene: Exploring Efficient Generation of Unbounded Outdoor Scenes
Han-Hung Lee, Qinghong Han, Angel X. Chang
In this paper, we explore the task of generating expansive outdoor scenes, ranging from castles to high-rises. Unlike indoor scene generation, which has been a primary focus of pri…
SceneEval: Evaluating Semantic Coherence in Text-Conditioned 3D Indoor Scene Synthesis
Hou In Ivan Tam, Hou In Derek Pun, Austin T. Wang +2
Despite recent advances in text-conditioned 3D indoor scene generation, there remain gaps in the evaluation of these methods. Existing metrics often measure realism by comparing ge…
Learning to Place Objects with Programs and Iterative Self Training
Adrian Chang, Kai Wang, Yuanbo Li +3
In this work we study indoor scene object placement. Given a 3D indoor scene and an object, the task is to predict placement locations within the scene. Empirical observations of d…
Enhancing DNA Foundation Models to Address Masking Inefficiencies
Monireh Safari, Pablo Millan Arias, Scott C. Lowe +3
Masked language modelling (MLM) as a pretraining objective has been widely adopted in genomic sequence modelling. While pretrained models can successfully serve as encoders for var…
Semantic Mapping in Indoor Embodied AI -- A Survey on Advances, Challenges, and Future Directions
Sonia Raychaudhuri, Angel X. Chang
Intelligent embodied agents (e.g. robots) need to perform complex semantic tasks in unfamiliar environments. Among many skills that the agents need to possess, building and maintai…
ViGiL3D: A Linguistically Diverse Dataset for 3D Visual Grounding
Austin T. Wang, ZeMing Gong, Angel X. Chang
3D visual grounding (3DVG) involves localizing entities in a 3D scene referred to by natural language text. Such models are useful for embodied AI and scene retrieval applications,…