211 citations · 576 across the 18 of their papers we have counts for
18 papers
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients
Sima Behpour, Thang Doan, Xin Li +3
Detecting out-of-distribution (OOD) data is crucial for ensuring the safe deployment of machine learning models in real-world applications. However, existing OOD detection approach…
UP-DP: Unsupervised Prompt Learning for Data Pre-Selection with Vision-Language Models
Xin Li, Sima Behpour, Thang Doan +3
In this study, we investigate the task of data pre-selection, which aims to select instances for labeling from an unlabeled dataset through a single pass, thereby optimizing perfor…
Hyp-OW: Exploiting Hierarchical Structure Learning with Hyperbolic Distance Enhances Open World Object Detection
Thang Doan, Xin Li, Sima Behpour +3
Open World Object Detection (OWOD) is a challenging and realistic task that extends beyond the scope of standard Object Detection task. It involves detecting both known and unknown…
CLIP-S: Language-Guided Self-Supervised Semantic Segmentation
Wenbin He, Suphanut Jamonnak, Liang Gou +1
Existing semantic segmentation approaches are often limited by costly pixel-wise annotations and predefined classes. In this work, we present CLIP-S that leverages self-supervi…
Self-supervised Semantic Segmentation Grounded in Visual Concepts
Wenbin He, William Surmeier, Arvind Kumar Shekar +2
Unsupervised semantic segmentation requires assigning a label to every pixel without any human annotations. Despite recent advances in self-supervised representation learning for i…
Interactive Visual Pattern Search on Graph Data via Graph Representation Learning
Huan Song, Zeng Dai, Panpan Xu +1
Graphs are a ubiquitous data structure to model processes and relations in a wide range of domains. Examples include control-flow graphs in programs and semantic scene graphs in im…