Person

Jie Luo

This person is no longer with EPFL

Related publications (36)

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Semantics-Aware Spatial-Temporal Binaries for Cross-Modal Video Retrieval

Jie Luo, Yiyu Wang, Mengshi Qi

With the current exponential growth of video-based social networks, video retrieval using natural language is receiving ever-increasing attention. Most existing approaches tackle this task by extracting individual frame-level spatial features to represent ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

STC-GAN: Spatio-Temporally Coupled Generative Adversarial Networks for Predictive Scene Parsing

Jie Luo, Yiyu Wang, Mengshi Qi

Predictive scene parsing is a task of assigning pixel-level semantic labels to a future frame of a video. It has many applications in vision-based artificial intelligent systems, e.g., autonomous driving and robot navigation. Although previous work has sho ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Special Section on Social Media as Sensors

Daniel Gatica-Perez, Jie Luo

Social media have transformed the Web into an interactive sharing platform where users upload data and media, comment on, and share this content within their social circles. Each content item is associated with an abundance of metadata and related informat ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Open-ended Learning of Visual and Multi-modal Patterns

Jie Luo

A common trend in machine learning and pattern classification research is the exploitation of massive amounts of information in order to achieve an increase in performance. In particular, learning from huge collections of data obtained from the web, and us ...

Ecole polytechnique fédérale de Lausanne2011

Open-Ended Learning of Visual and Multi-Modal Patterns

Jie Luo

EPFL2011

Learning from Images with Captions Using the Maximum Margin Set Algorithm

Barbara Caputo, Jie Luo, Vittorio Ferrari

A large amount of images with accompanying text captions are available on the Internet. These are valuable for training visual classifiers without any explicit manual intervention. In this paper, we present a general framework to address this problem. Unde ...

Idiap2011

Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning

Jie Luo

Many state-of-the-art approaches for Multi Kernel Learning (MKL) struggle at finding a compromise between performance, sparsity of the solution and speed of the optimization process. In this paper we look at the MKL problem at the same time from a learning ...

2011

Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning

Jie Luo

Idiap2011

Multiclass Transfer Learning from Unconstrained Priors

Barbara Caputo, Jie Luo, Tatiana Tommasi

The vast majority of transfer learning methods proposed in the visual recognition domain over the last years ad- dresses the problem of object category detection, assuming a strong control over the priors from which transfer is done. This is a strict condi ...

2011

Multiclass Transfer Learning from Unconstrained Priors

Barbara Caputo, Jie Luo, Tatiana Tommasi

Idiap2011