30 citations · 33 across the 5 of their papers we have counts for
6 papers
Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes
Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong +2
A novel algorithm to detect road lanes in the eigenlane space is proposed in this paper. First, we introduce the notion of eigenlanes, which are data-driven descriptors for structu…
Harmonious Semantic Line Detection via Maximal Weight Clique Selection
Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong +1
A novel algorithm to detect an optimal set of semantic lines is proposed in this work. We develop two networks: selection network (S-Net) and harmonization network (H-Net). First,…
Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation
Seungmin Lee, Dongwan Kim, Namil Kim +1
Recent works on domain adaptation exploit adversarial training to obtain domain-invariant feature representations from the joint learning of feature extractor and domain discrimina…
Anchor Loss: Modulating Loss Scale based on Prediction Difficulty
Serim Ryou, Seong-Gyun Jeong, Pietro Perona
We propose a novel loss function that dynamically rescales the cross entropy based on prediction difficulty regarding a sample. Deep neural network architectures in image classific…
End-to-end Learning of Image based Lane-Change Decision
Seong-Gyun Jeong, Jiwon Kim, Sujung Kim +1
We propose an image based end-to-end learning framework that helps lane-change decisions for human drivers and autonomous vehicles. The proposed system, Safe Lane-Change Aid Networ…
Progressive Tree-like Curvilinear Structure Reconstruction with Structured Ranking Learning and Graph Algorithm
Seong-Gyun Jeong, Yuliya Tarabalka, Nicolas Nisse +1
We propose a novel tree-like curvilinear structure reconstruction algorithm based on supervised learning and graph theory. In this work we analyze image patches to obtain the local…