18 citations · 54 across the 13 of their papers we have counts for
5 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…
PointFix: Learning to Fix Domain Bias for Robust Online Stereo Adaptation
Kwonyoung Kim, Jungin Park, Jiyoung Lee +2
Online stereo adaptation tackles the domain shift problem, caused by different environments between synthetic (training) and real (test) datasets, to promptly adapt stereo models i…
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…