22 citations · 67 across the 13 of their papers we have counts for
6 papers · 1 filter
InterHier: Learning Interconnected Hierarchical Semantics for Open-Vocabulary Object Detection
Yeong-Jin Kim, Ho-Joong Kim, Seong-Whan Lee
In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations for open-vocabulary object detection. Existing methods esta…
Semantic Prioritization in Visual Counterfactual Explanations with Weighted Segmentation and Auto-Adaptive Region Selection
Lintong Zhang, Kang Yin, Seong-Whan Lee
In the domain of non-generative visual counterfactual explanations (CE), traditional techniques frequently involve the substitution of sections within a query image with correspond…
Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers
Heejo Kong, Sung-Jin Kim, Gunho Jung +1
Conventional semi-supervised learning (SSL) ideally assumes that labeled and unlabeled data share an identical class distribution, however in practice, this assumption is easily vi…
Explaining generative diffusion models via visual analysis for interpretable decision-making process
Ji-Hoon Park, Yeong-Joon Ju, Seong-Whan Lee
Diffusion models have demonstrated remarkable performance in generation tasks. Nevertheless, explaining the diffusion process remains challenging due to it being a sequence of deno…
AM-SORT: Adaptable Motion Predictor with Historical Trajectory Embedding for Multi-Object Tracking
Vitaliy Kim, Gunho Jung, Seong-Whan Lee
Many multi-object tracking (MOT) approaches, which employ the Kalman Filter as a motion predictor, assume constant velocity and Gaussian-distributed filtering noises. These assumpt…
NeuroInspect: Interpretable Neuron-based Debugging Framework through Class-conditional Visualizations
Yeong-Joon Ju, Ji-Hoon Park, Seong-Whan Lee
Despite deep learning (DL) has achieved remarkable progress in various domains, the DL models are still prone to making mistakes. This issue necessitates effective debugging tools…