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ORCIDJulieta Martinez
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2020 – today
- 2024
[i8]Rawal Khirodkar, Timur M. Bagautdinov, Julieta Martinez, Su Zhaoen, Austin James, Peter Selednik, Stuart Anderson, Shunsuke Saito:
Sapiens: Foundation for Human Vision Models. CoRR abs/2408.12569 (2024)- 2021
- [c13]John Phillips, Julieta Martinez, Ioan Andrei Barsan, Sergio Casas, Abbas Sadat, Raquel Urtasun:
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction. CVPR 2021: 4679-4689 - [c12]Julieta Martinez, Jashan Shewakramani, Ting-Wei Liu, Ioan Andrei Barsan, Wenyuan Zeng, Raquel Urtasun:
Permute, Quantize, and Fine-Tune: Efficient Compression of Neural Networks. CVPR 2021: 15699-15708 - [i7]John Phillips, Julieta Martinez, Ioan Andrei Bârsan, Sergio Casas, Abbas Sadat, Raquel Urtasun:
Deep Multi-Task Learning for Joint Localization, Perception, and Prediction. CoRR abs/2101.06720 (2021) - 2020
- [c11]Julieta Martinez, Sasha Doubov, Jack Fan, Ioan Andrei Bârsan, Shenlong Wang, Gellért Máttyus, Raquel Urtasun:
Pit30M: A Benchmark for Global Localization in the Age of Self-Driving Cars. IROS 2020: 4477-4484 - [i6]Julieta Martinez, Jashan Shewakramani, Ting-Wei Liu, Ioan Andrei Bârsan, Wenyuan Zeng, Raquel Urtasun:
Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks. CoRR abs/2010.15703 (2020) - [i5]Xinkai Wei, Ioan Andrei Bârsan, Shenlong Wang, Julieta Martinez, Raquel Urtasun:
Learning to Localize Through Compressed Binary Maps. CoRR abs/2012.10942 (2020) - [i4]Julieta Martinez, Sasha Doubov, Jack Fan, Ioan Andrei Bârsan, Shenlong Wang, Gellért Máttyus, Raquel Urtasun:
Pit30M: A Benchmark for Global Localization in the Age of Self-Driving Cars. CoRR abs/2012.12437 (2020)
2010 – 2019
- 2019
- [c10]Xinkai Wei, Ioan Andrei Barsan, Shenlong Wang, Julieta Martinez, Raquel Urtasun:
Learning to Localize Through Compressed Binary Maps. CVPR 2019: 10316-10324 - 2018
- [c9]Julieta Martinez, Shobhit Zakhmi, Holger H. Hoos, James J. Little:
LSQ++: Lower Running Time and Higher Recall in Multi-codebook Quantization. ECCV (16) 2018: 508-523 - 2017
- [c8]Julieta Martinez, Michael J. Black, Javier Romero:
On Human Motion Prediction Using Recurrent Neural Networks. CVPR 2017: 4674-4683 - [c7]Julieta Martinez, Rayat Hossain, Javier Romero, James J. Little:
A Simple Yet Effective Baseline for 3d Human Pose Estimation. ICCV 2017: 2659-2668 - [i3]Julieta Martinez, Michael J. Black, Javier Romero:
On human motion prediction using recurrent neural networks. CoRR abs/1705.02445 (2017) - [i2]Julieta Martinez, Rayat Hossain, Javier Romero, James J. Little:
A simple yet effective baseline for 3d human pose estimation. CoRR abs/1705.03098 (2017) - 2016
- [c6]Julieta Martinez, Joris Clement, Holger H. Hoos, James J. Little:
Revisiting Additive Quantization. ECCV (2) 2016: 137-153 - [c5]Julieta Martinez, Holger H. Hoos, James J. Little:
Solving Multi-codebook Quantization in the GPU. ECCV Workshops (1) 2016: 638-650 - [c4]Ankur Gupta, John He, Julieta Martinez, James J. Little, Robert J. Woodham:
Efficient video-based retrieval of human motion with flexible alignment. WACV 2016: 1-9 - 2015
- [c3]Frederick Tung, Julieta Martinez, Holger H. Hoos, James J. Little:
Bank of Quantization Models: A Data-Specific Approach to Learning Binary Codes for Large-Scale Retrieval Applications. WACV 2015: 566-571 - 2014
- [c2]Ankur Gupta, Julieta Martinez, James J. Little, Robert J. Woodham:
3D Pose from Motion for Cross-View Action Recognition via Non-linear Circulant Temporal Encoding. CVPR 2014: 2601-2608 - [c1]Julieta Martinez, James J. Little, Nando de Freitas:
Bayesian Optimization with an Empirical Hardness Model for approximate Nearest Neighbour Search. WACV 2014: 588-595 - [i1]Julieta Martinez, Holger H. Hoos, James J. Little:
Stacked Quantizers for Compositional Vector Compression. CoRR abs/1411.2173 (2014)
Coauthor Index
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