7 papers
AU-Guided Synthetic Video Generation for Micro-Expression Recognition
Pei-Sze Tan, Sailaja Rajanala, Yee-Fan Tan +2
Micro-expression recognition is limited by the small scale, narrow demographic coverage, and restricted emotion labels of existing datasets. We introduce EquiME, a synthetic micro-…
Forgive or forget: Understanding the context of hate in audio retrieval systems
Arghya Pal, Sailaja Rajanala, Raphael C. -W. Phan +1
Handling toxic retrieval in text-to-audio systems is challenging due to contextual dependencies. Existing strategies (e.g., rephrasing, summarization) risk altering intent or omitt…
FORTE: FOL-guided Optimal Refinement for Text-audio rEtrieval
Arghya Pal, Sailaja Rajanala
Text-to-audio retrieval has made significant progress with shared embedding models such as CLAP and Pengi, yet they often struggle with fine-grained semantic alignment due to the i…
RECIPER: A Dual-View Retrieval Pipeline for Procedure-Oriented Materials Question Answering
Zhuoyu Wu, Wenhui Ou, Pei-Sze Tan +3
Retrieving procedure-oriented evidence from materials science papers is difficult because key synthesis details are often scattered across long, context-heavy documents and are not…
FLAG-4D: Flow-Guided Local-Global Dual-Deformation Model for 4D Reconstruction
Guan Yuan Tan, Ngoc Tuan Vu, Arghya Pal +4
We introduce FLAG-4D, a novel framework for generating novel views of dynamic scenes by reconstructing how 3D Gaussian primitives evolve through space and time. Existing methods ty…
Causal-Ex: Causal Graph-based Micro and Macro Expression Spotting
Pei-Sze Tan, Sailaja Rajanala, Arghya Pal +2
Detecting concealed emotions within apparently normal expressions is crucial for identifying potential mental health issues and facilitating timely support and intervention. The ta…