20 citations · 26 across the 17 of their papers we have counts for
5 papers · 1 filter
Vicinity-Guided Discriminative Latent Diffusion for Privacy-Preserving Domain Adaptation
Jing Wang, Wonho Bae, Jiahong Chen +2
Recent work on latent diffusion models (LDMs) has focused almost exclusively on generative tasks, leaving their potential for discriminative transfer largely unexplored. We introdu…
Beyond Softmax: Dual-Branch Sigmoid Architecture for Accurate Class Activation Maps
Yoojin Oh, Junhyug Noh
Class Activation Mapping (CAM) and its extensions have become indispensable tools for visualizing the evidence behind deep network predictions. However, by relying on a final softm…
Pinpointing Trigger Moment for Grounded Video QA: Enhancing Spatio-temporal Grounding in Multimodal Large Language Models
Jinhwan Seo, Yoonki Cho, Junhyug Noh +1
In this technical report, we introduce a framework to address Grounded Video Question Answering (GVQA) task for the ICCV 2025 Perception Test Challenge. The GVQA task demands robus…
Diffusion-Driven Two-Stage Active Learning for Low-Budget Semantic Segmentation
Jeongin Kim, Wonho Bae, YouLee Han +4
Semantic segmentation demands dense pixel-level annotations, which can be prohibitively expensive - especially under extremely constrained labeling budgets. In this paper, we addre…
SteeringTTA: Guiding Diffusion Trajectories for Robust Test-Time-Adaptation
Jihyun Yu, Yoojin Oh, Wonho Bae +2
Test-time adaptation (TTA) aims to correct performance degradation of deep models under distribution shifts by updating models or inputs using unlabeled test data. Input-only diffu…