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Seonghoon Yu

4 accepted papers

2025

Latent Expression Generation for Referring Image Segmentation and Grounding

ICCV 2025poster

Visual grounding tasks, such as referring image segmentation (RIS) and referring expression comprehension (REC), aim to localize a target object based on a given textual description. The target object in an image can be described in multiple ways, reflecting diverse attributes such as color, positio…

Cited by 0SourcePDFScholar
2025

Single-Teacher View Augmentation: Boosting Knowledge Distillation via Angular Diversity

NeurIPS 2025poster

Knowledge Distillation (KD) aims to train a lightweight student model by transferring knowledge from a large, high-capacity teacher. Recent studies have shown that leveraging diverse teacher perspectives can significantly improve distillation performance; however, achieving such diversity typically…

Cited by 0SourceScholar
2024

Pseudo-RIS: Distinctive Pseudo-supervision Generation for Referring Image Segmentation

ECCV 2024poster

"We propose a new framework that automatically generates high-quality segmentation masks with their referring expressions as pseudo supervisions for referring image segmentation (RIS). These pseudo supervisions allow the training of any supervised RIS methods without the cost of manual labeling. To…

2023

Zero-Shot Referring Image Segmentation With Global-Local Context Features

CVPR 2023poster

Referring image segmentation (RIS) aims to find a segmentation mask given a referring expression grounded to a region of the input image. Collecting labelled datasets for this task, however, is notoriously costly and labor-intensive. To overcome this issue, we propose a simple yet effective zero-sho…