2 citations · 5 across the 8 of their papers we have counts for
4 papers · 1 filter
MSI: Maximize Support-Set Information for Few-Shot Segmentation
Seonghyeon Moon, Samuel S. Sohn, Honglu Zhou +4
FSS(Few-shot segmentation) aims to segment a target class using a small number of labeled images(support set). To extract information relevant to the target class, a dominant appro…
An Information-Theoretic Approach for Estimating Scenario Generalization in Crowd Motion Prediction
Gang Qiao, Kaidong Hu, Seonghyeon Moon +4
Learning-based approaches to modeling crowd motion have become increasingly successful but require training and evaluation on large datasets, coupled with complex model selection a…
HM: Hybrid Masking for Few-Shot Segmentation
Seonghyeon Moon, Samuel S. Sohn, Honglu Zhou +4
We study few-shot semantic segmentation that aims to segment a target object from a query image when provided with a few annotated support images of the target class. Several recen…
MUSE-VAE: Multi-Scale VAE for Environment-Aware Long Term Trajectory Prediction
Mihee Lee, Samuel S. Sohn, Seonghyeon Moon +3
Accurate long-term trajectory prediction in complex scenes, where multiple agents (e.g., pedestrians or vehicles) interact with each other and the environment while attempting to a…