18 citations · 76 across the 42 of their papers we have counts for
5 papers · 2 filters
Countering Multi-modal Representation Collapse through Rank-targeted Fusion
Seulgi Kim, Kiran Kokilepersaud, Mohit Prabhushankar +1
Multi-modal fusion methods often suffer from two types of representation collapse: feature collapse where individual dimensions lose their discriminative power (as measured by eige…
Subject Invariant Contrastive Learning for Human Activity Recognition
Yavuz Yarici, Kiran Kokilepersaud, Mohit Prabhushankar +1
The high cost of annotating data makes self-supervised approaches, such as contrastive learning methods, appealing for Human Activity Recognition (HAR). Effective contrastive learn…
Multi-level and Multi-modal Action Anticipation
Seulgi Kim, Ghazal Kaviani, Mohit Prabhushankar +1
Action anticipation, the task of predicting future actions from partially observed videos, is crucial for advancing intelligent systems. Unlike action recognition, which operates o…
A Large-scale Benchmark on Geological Fault Delineation Models: Domain Shift, Training Dynamics, Generalizability, Evaluation and Inferential Behavior
Jorge Quesada, Chen Zhou, Prithwijit Chowdhury +5
Machine learning has taken a critical role in seismic interpretation workflows, especially in fault delineation tasks. However, despite the recent proliferation of pretrained model…
Hierarchical and Multimodal Data for Daily Activity Understanding
Ghazal Kaviani, Yavuz Yarici, Seulgi Kim +4
Daily Activity Recordings for Artificial Intelligence (DARai, pronounced "Dahr-ree") is a multimodal, hierarchically annotated dataset constructed to understand human activities in…