4 citations · 6 across the 5 of their papers we have counts for
5 papers
Rethinking Open-World Semi-Supervised Learning: Distribution Mismatch and Inductive Inference
Seongheon Park, Hyuk Kwon, Kwanghoon Sohn +1
Open-world semi-supervised learning (OWSSL) extends conventional semi-supervised learning to open-world scenarios by taking account of novel categories in unlabeled datasets. Despi…
Hierarchical Visual Primitive Experts for Compositional Zero-Shot Learning
Hanjae Kim, Jiyoung Lee, Seongheon Park +1
Compositional zero-shot learning (CZSL) aims to recognize unseen compositions with prior knowledge of known primitives (attribute and object). Previous works for CZSL often suffer…
PartMix: Regularization Strategy to Learn Part Discovery for Visible-Infrared Person Re-identification
Minsu Kim, Seungryong Kim, JungIn Park +2
Modern data augmentation using a mixture-based technique can regularize the models from overfitting to the training data in various computer vision applications, but a proper data…
IFSeg: Image-free Semantic Segmentation via Vision-Language Model
Sukmin Yun, Seong Hyeon Park, Paul Hongsuck Seo +1
Vision-language (VL) pre-training has recently gained much attention for its transferability and flexibility in novel concepts (e.g., cross-modality transfer) across various visual…
Language-free Training for Zero-shot Video Grounding
Dahye Kim, Jungin Park, Jiyoung Lee +2
Given an untrimmed video and a language query depicting a specific temporal moment in the video, video grounding aims to localize the time interval by understanding the text and vi…