Search Results for author: Julieta Martinez

Found 9 papers, 6 papers with code

Deep Multi-Task Learning for Joint Localization, Perception, and Prediction

no code implementations CVPR 2021 John Phillips, Julieta Martinez, Ioan Andrei Bârsan, Sergio Casas, Abbas Sadat, Raquel Urtasun

Over the last few years, we have witnessed tremendous progress on many subtasks of autonomous driving, including perception, motion forecasting, and motion planning.

Motion Forecasting Motion Planning +1

Learning to Localize Through Compressed Binary Maps

no code implementations CVPR 2019 Xinkai Wei, Ioan Andrei Bârsan, Shenlong Wang, Julieta Martinez, Raquel Urtasun

One of the main difficulties of scaling current localization systems to large environments is the on-board storage required for the maps.

LSQ++: Lower running time and higher recall in multi-codebook quantization

1 code implementation ECCV 2018 Julieta Martinez, Shobhit Zakhmi, Holger H. Hoos, James J. Little

Multi-codebook quantization (MCQ) is the task of expressing a set of vectors as accurately as possible in terms of discrete entries in multiple bases.


A simple yet effective baseline for 3d human pose estimation

12 code implementations ICCV 2017 Julieta Martinez, Rayat Hossain, Javier Romero, James J. Little

Following the success of deep convolutional networks, state-of-the-art methods for 3d human pose estimation have focused on deep end-to-end systems that predict 3d joint locations given raw image pixels.

3D Pose Estimation Monocular 3D Human Pose Estimation

On human motion prediction using recurrent neural networks

6 code implementations CVPR 2017 Julieta Martinez, Michael J. Black, Javier Romero

Human motion modelling is a classical problem at the intersection of graphics and computer vision, with applications spanning human-computer interaction, motion synthesis, and motion prediction for virtual and augmented reality.

Human motion prediction Motion Estimation +2

Stacked Quantizers for Compositional Vector Compression

2 code implementations8 Nov 2014 Julieta Martinez, Holger H. Hoos, James J. Little

Recently, Babenko and Lempitsky introduced Additive Quantization (AQ), a generalization of Product Quantization (PQ) where a non-independent set of codebooks is used to compress vectors into small binary codes.


3D Pose from Motion for Cross-view Action Recognition via Non-linear Circulant Temporal Encoding

1 code implementation CVPR 2014 Ankur Gupta, Julieta Martinez, James J. Little, Robert J. Woodham

We describe a new approach to transfer knowledge across views for action recognition by using examples from a large collection of unlabelled mocap data.

Action Recognition

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