18 citations · 53 across the 11 of their papers we have counts for
16 papers · 1 filter
Neural Matching Fields: Implicit Representation of Matching Fields for Visual Correspondence
Sunghwan Hong, Jisu Nam, Seokju Cho +4
Existing pipelines of semantic correspondence commonly include extracting high-level semantic features for the invariance against intra-class variations and background clutters. Th…
Contour-Aware Equipotential Learning for Semantic Segmentation
Xu Yin, Dongbo Min, Yuchi Huo +1
With increasing demands for high-quality semantic segmentation in the industry, hard-distinguishing semantic boundaries have posed a significant threat to existing solutions. Inspi…
Sequential Cross Attention Based Multi-task Learning
Sunkyung Kim, Hyesong Choi, Dongbo Min
In multi-task learning (MTL) for visual scene understanding, it is crucial to transfer useful information between multiple tasks with minimal interferences. In this paper, we propo…
Pin the Memory: Learning to Generalize Semantic Segmentation
Jin Kim, Jiyoung Lee, Jungin Park +2
The rise of deep neural networks has led to several breakthroughs for semantic segmentation. In spite of this, a model trained on source domain often fails to work properly in new…
DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenes
Jaehoon Cho, Dongbo Min, Youngjung Kim +1
This manual is intended to provide a detailed description of the DIML/CVL RGB-D dataset. This dataset is comprised of 2M color images and their corresponding depth maps from a grea…
Self-balanced Learning For Domain Generalization
Jin Kim, Jiyoung Lee, Jungin Park +2
Domain generalization aims to learn a prediction model on multi-domain source data such that the model can generalize to a target domain with unknown statistics. Most existing appr…