4 citations · 11 across the 7 of their papers we have counts for
9 papers
Scaling Diverse Language Generation for 3D Visual Grounding
Austin T. Wang, Dongchen Yang, Angel X. Chang
Developing robust models for 3D visual grounding (3DVG), the localization of entities in a 3D scene described in natural language, is important for enabling agents to correspond sp…
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…
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…
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…
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,…
SceneMotifCoder: Example-driven Visual Program Learning for Generating 3D Object Arrangements
Hou In Ivan Tam, Hou In Derek Pun, Austin T. Wang +2
Despite advances in text-to-3D generation methods, generation of multi-object arrangements remains challenging. Current methods exhibit failures in generating physically plausible…
BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity
Zahra Gharaee, Scott C. Lowe, ZeMing Gong +10
As part of an ongoing worldwide effort to comprehend and monitor insect biodiversity, this paper presents the BIOSCAN-5M Insect dataset to the machine learning community and establ…
CLIBD: Bridging Vision and Genomics for Biodiversity Monitoring at Scale
ZeMing Gong, Austin T. Wang, Xiaoliang Huo +4
Measuring biodiversity is crucial for understanding ecosystem health. While prior works have developed machine learning models for taxonomic classification of photographic images a…
BarcodeBERT: Transformers for Biodiversity Analysis
Pablo Millan Arias, Niousha Sadjadi, Monireh Safari +9
In the global challenge of understanding and characterizing biodiversity, short species-specific genomic sequences known as DNA barcodes play a critical role, enabling fine-grained…