3 papers
eess.AS2026
Learning What To Hear: Boosting Sound-Source Association For Robust Audiovisual Instance Segmentation
Jinbae Seo, Hyeongjun Kwon, Kwonyoung Kim +2
Audiovisual instance segmentation (AVIS) requires accurately localizing and tracking sounding objects throughout video sequences. Existing methods suffer from visual bias stemming…
cs.CV2025
Faster Parameter-Efficient Tuning with Token Redundancy Reduction
Kwonyoung Kim, Jungin Park, Jin Kim +2
Parameter-efficient tuning (PET) aims to transfer pre-trained foundation models to downstream tasks by learning a small number of parameters. Compared to traditional fine-tuning, w…
cs.CV2025
PointFix: Learning to Fix Domain Bias for Robust Online Stereo Adaptation
Kwonyoung Kim, Jungin Park, Jiyoung Lee +2
Online stereo adaptation tackles the domain shift problem, caused by different environments between synthetic (training) and real (test) datasets, to promptly adapt stereo models i…