6 papers
Explicit World Models for Reliable Human-Robot Collaboration
Kenneth Kwok, Basura Fernando, Qianli Xu +3
This paper addresses the topic of robustness under sensing noise, ambiguous instructions, and human-robot interaction. We take a radically different tack to the issue of reliable e…
VOST-SGG: VLM-Aided One-Stage Spatio-Temporal Scene Graph Generation
Chinthani Sugandhika, Chen Li, Deepu Rajan +1
Spatio-temporal scene graph generation (ST-SGG) aims to model objects and their evolving relationships across video frames, enabling interpretable representations for downstream re…
HMR3D: Hierarchical Multimodal Representation for 3D Scene Understanding with Large Vision-Language Model
Chen Li, Eric Peh, Basura Fernando
Recent advances in large vision-language models (VLMs) have shown significant promise for 3D scene understanding. Existing VLM-based approaches typically align 3D scene features wi…
Mitigating Easy Option Bias in Multiple-Choice Question Answering
Hao Zhang, Chen Li, Basura Fernando
In this early study, we observe an Easy-Options Bias (EOB) issue in some multiple-choice Visual Question Answering (VQA) benchmarks such as MMStar, RealWorldQA, SEED-Bench, Next-QA…
IMoRe: Implicit Program-Guided Reasoning for Human Motion Q&A
Chen Li, Chinthani Sugandhika, Yeo Keat Ee +5
Existing human motion Q\&A methods rely on explicit program execution, where the requirement for manually defined functional modules may limit the scalability and adaptability. To…
Neuro Symbolic Knowledge Reasoning for Procedural Video Question Answering
Basura Fernando, Thanh-Son Nguyen, Hong Yang +3
In this work we present Knowledge Module Learning (KML) to understand and reason over procedural tasks that requires models to learn structured and compositional procedural knowled…