Hi! I'm Julieta

Since January 2015, I've been a PhD student in the Department of Computer Science at the University of British Columbia.

I am supervised by Jim Little and Holger Hoos. I do research in computer vision.

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Research

Selected publications

Human motion prediction

Julieta Martinez, Michael J. Black, Javier Romero.
On human motion prediction using recurrent neural networks. In CVPR 2017 (29.84% acceptance rate)

We take a close look at deep recurrent approaches for human motion prediction, and propose a simple and scalable architecture that outperforms the state of the art.

Code and paper coming up.

Revisiting AQ

Julieta Martinez, Joris Clement, Holger H. Hoos, James J. Little.
Revisiting additive quantization. In ECCV 2016 (26.6% acceptance rate)

We introduce an optimization method for additive quantization that pushes it beyond the state of the art.

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3D pose from motion

Ankur Gupta*, Julieta Martinez*, James J. Little, Robert J. Woodham.
3D pose from motion for cross-view action recognition. In CVPR 2014 (29.88% acceptance rate)

An approach to improving cross-view action recognition by retrieving mocap given video sequences.

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Other publications

Mocap retrieval

Ankur Gupta, John He, Julieta Martinez, James J. Little and Robert J. Woodham.
Efficient video-based retrieval of human motion with flexible alignment. In WACV 2016

We formalize the problem of video-based mocap retrieval. We also investigate different retrieval methods for this task.

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Stacked quantizers

Julieta Martinez, Holger H. Hoos and James J. Little. Stacked quantizers for compositional vector compression. In arxiv (2014)

Some of my early attempts to improve multi-codebook quantization. This approach is equivalent to enhanced RVQ, and has been superceeded by our work on revisiting AQ. The code is very accessible though!

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Yet more publications

    Solving multi-codebook quantization in the GPU .bib

    Julieta Martinez, Holger H. Hoos and James J. Little. In 4th Workshop on Web-scale Vision and Social Media (VSM), at ECCV 2016.

    Complement to our work on Revisiting AQ. Details our GPU implementation.

    Hash bank .bib

    Frederick Tung, Julieta Martinez, Holger H. Hoos and James J. Little. In WACV 2015.

    A vector is mapped to one of many hash functions, which improves accuracy at increased query time.

    BO on FLANN .bib

    Julieta Martinez, James J. Little and Nando de Freitas. In WACV 2014.

    We showed that Bayesian optimization with Gaussian processes would be a great addition to FLANN.

Misc

DeepViz

My information visualization final project, taught by the wonderful Tamara Munzner. A javascript visualization tool for image retrieval (2015).

Efros and Leung JS

A javascript implementation of a classic method for texture synthesis (2015).

Pavlov is no simpleton

I tried to reproduce the results of a 1993 paper on evolutionary dynamics by Sigmund and Novak. I also wrote a blog post about it (2014).

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