most citedPartMix: Regularization Strategy to Learn Part Discovery for Visible-Infrared Person Re-identification

4 citations · 8 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV20241 cited

Enhancing Source-Free Domain Adaptive Object Detection with Low-confidence Pseudo Label Distillation

Ilhoon Yoon, Hyeongjun Kwon, Jin Kim +3

Source-Free domain adaptive Object Detection (SFOD) is a promising strategy for deploying trained detectors to new, unlabeled domains without accessing source data, addressing sign…

cs.CV2024

Improving Visual Recognition with Hyperbolical Visual Hierarchy Mapping

Hyeongjun Kwon, Jinhyun Jang, Jin Kim +2

Visual scenes are naturally organized in a hierarchy, where a coarse semantic is recursively comprised of several fine details. Exploring such a visual hierarchy is crucial to reco…

cs.CV20233 cited

Knowing Where to Focus: Event-aware Transformer for Video Grounding

Jinhyun Jang, Jungin Park, Jin Kim +2

Recent DETR-based video grounding models have made the model directly predict moment timestamps without any hand-crafted components, such as a pre-defined proposal or non-maximum s…

cs.CV2023

Semantic-aware Network for Aerial-to-Ground Image Synthesis

Jinhyun Jang, Taeyong Song, Kwanghoon Sohn

Aerial-to-ground image synthesis is an emerging and challenging problem that aims to synthesize a ground image from an aerial image. Due to the highly different layout and object r…

cs.CV2023

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…

cs.CV20234 cited

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…