Publications by Yunpeng Li | EPFL Graph Search

Related publications (7)

Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets

We propose a working set based approximate subgradient descent algorithm to minimize the margin-sensitive hinge loss arising from the soft constraints in max-margin learning frameworks, such as the structured SVM. We focus on the setting of general graphic ...

2013

A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery

Yinlin Hu, Yunpeng Li

Semantic segmentation for remote sensing images (RSI) is critical for the Earth monitoring system. However, the covariate shift between RSI datasets under different capture conditions cannot be alleviated by directly using the unsupervised domain adaptatio ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

The Sixth Visual Object Tracking VOT2018 Challenge Results

Wei Wu, Qiang Wang, Bo Li, Yunpeng Li, Feng Li, Erhan Gündogdu

The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Worldwide Pose Estimation Using 3D Point Clouds

Pascal Fua, Yunpeng Li

We address the problem of determining where a photo was taken by estimating a full 6-DOF-plus-intrincs camera pose with respect to a large geo-registered 3D point cloud, bringing together research on image localization, landmark recognition, and 3D pose es ...

2012

CIDRE: an illumination-correction method for optical microscopy

Kevin Smith, Yunpeng Li

Uneven illumination affects every image acquired by a microscope. It is often overlooked, but it can introduce considerable bias to image measurements. The most reliable correction methods require special reference images, and retrospective alternatives do ...

Nature Publishing Group2015

Learning Structured Models for Segmentation of 2D and 3D Imagery

Pascal Fua, Graham Knott, Carlos Joaquin Becker, Kevin Smith, Aurélien Lucchi, Pablo Marquez Neila, Yunpeng Li

Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to image segmentation use structured models whose parameters must be carefully chosen for optimal perfo ...

Institute of Electrical and Electronics Engineers2015

Structured Image Segmentation using Kernelized Features

Pascal Fua, Kevin Smith, Aurélien Lucchi, Yunpeng Li

Most state-of-the-art approaches to image segmentation formulate the problem using Conditional Random Fields. These models typically include a unary term and a pairwise term, whose parameters must be carefully chosen for optimal performance. Recently, stru ...

2012