Search Results for author: Won-Dong Jang

Found 15 papers, 3 papers with code

Dynamic High-Pass Filtering and Multi-Spectral Attention for Image Super-Resolution

no code implementations ICCV 2021 Salma Abdel Magid, Yulun Zhang, Donglai Wei, Won-Dong Jang, Zudi Lin, Yun Fu, Hanspeter Pfister

Specifically, we propose a dynamic high-pass filtering (HPF) module that locally applies adaptive filter weights for each spatial location and channel group to preserve high-frequency signals.

Image Super-Resolution

A Topological Nomenclature for 3D Shape Analysis in Connectomics

1 code implementation27 Sep 2019 Abhimanyu Talwar, Zudi Lin, Donglai Wei, Yuesong Wu, Bowen Zheng, Jinglin Zhao, Won-Dong Jang, Xueying Wang, Jeff W. Lichtman, Hanspeter Pfister

Next, we develop nomenclature rules for pyramidal neurons and mitochondria from the reduced graph and finally learn the feature embedding for shape manipulation.

3D Shape Classification 3D Shape Retrieval

Interactive Image Segmentation via Backpropagating Refinement Scheme

no code implementations CVPR 2019 Won-Dong Jang, Chang-Su Kim

An interactive image segmentation algorithm, which accepts user-annotations about a target object and the background, is proposed in this work.

Interactive Segmentation Semantic Segmentation

Temporal Superpixels Based on Proximity-Weighted Patch Matching

no code implementations ICCV 2017 Se-Ho Lee, Won-Dong Jang, Chang-Su Kim

A temporal superpixel algorithm based on proximity-weighted patch matching (TS-PPM) is proposed in this work.

Frame Patch Matching +1

Contour-Constrained Superpixels for Image and Video Processing

no code implementations CVPR 2017 Se-Ho Lee, Won-Dong Jang, Chang-Su Kim

We initialize superpixel labels in each frame by transferring those in the previous frame and refine the labels to make superpixels temporally consistent as well as compatible with object contours.

Frame Superpixels

Online Video Object Segmentation via Convolutional Trident Network

no code implementations CVPR 2017 Won-Dong Jang, Chang-Su Kim

A semi-supervised online video object segmentation algorithm, which accepts user annotations about a target object at the first frame, is proposed in this work.

Frame Optical Flow Estimation +3

Multiple Random Walkers and Their Application to Image Cosegmentation

no code implementations CVPR 2015 Chulwoo Lee, Won-Dong Jang, Jae-Young Sim, Chang-Su Kim

A graph-based system to simulate the movements and interactions of multiple random walkers (MRW) is proposed in this work.

Cannot find the paper you are looking for? You can Submit a new open access paper.