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Books and Theses
- 2017
[b1]Catalin Ionescu:
Large scale structured models for computer vision. University of Bonn, Germany, 2017, pp. 1-100
Journal Articles
- 2014
- [j1]Catalin Ionescu, Dragos Papava, Vlad Olaru, Cristian Sminchisescu:
Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments. IEEE Trans. Pattern Anal. Mach. Intell. 36(7): 1325-1339 (2014)
Conference and Workshop Papers
- 2024
- [c12]João Carreira, Michael King, Viorica Patraucean, Dilara Gokay, Catalin Ionescu, Yi Yang, Daniel Zoran, Joseph Heyward, Carl Doersch, Yusuf Aytar, Dima Damen, Andrew Zisserman:
Learning from One Continuous Video Stream. CVPR 2024: 28751-28761 - 2022
- [c11]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. ICLR 2022 - 2020
- [c10]Brendan O'Donoghue, Ian Osband, Catalin Ionescu:
Making Sense of Reinforcement Learning and Probabilistic Inference. ICLR 2020 - 2019
- [c9]David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih:
Unsupervised Control Through Non-Parametric Discriminative Rewards. ICLR (Poster) 2019 - [c8]Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih:
Unsupervised Learning of Object Keypoints for Perception and Control. NeurIPS 2019: 10723-10733 - 2017
- [c7]Catalin Ionescu, Alin-Ionut Popa, Cristian Sminchisescu:
Large-Scale Data-Dependent Kernel Approximation. AISTATS 2017: 19-27 - 2016
- [c6]Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu:
Using Fast Weights to Attend to the Recent Past. NIPS 2016: 4331-4339 - 2015
- [c5]Catalin Ionescu, Orestis Vantzos, Cristian Sminchisescu:
Matrix Backpropagation for Deep Networks with Structured Layers. ICCV 2015: 2965-2973 - 2014
- [c4]Catalin Ionescu, João Carreira, Cristian Sminchisescu:
Iterated Second-Order Label Sensitive Pooling for 3D Human Pose Estimation. CVPR 2014: 1661-1668 - 2011
- [c3]Catalin Ionescu, Fuxin Li, Cristian Sminchisescu:
Latent structured models for human pose estimation. ICCV 2011: 2220-2227 - 2010
- [c2]Fuxin Li, Catalin Ionescu, Cristian Sminchisescu:
Random Fourier Approximations for Skewed Multiplicative Histogram Kernels. DAGM-Symposium 2010: 262-271 - 2009
- [c1]Catalin Ionescu, Liefeng Bo, Cristian Sminchisescu:
Structural SVM for visual localization and continuous state estimation. ICCV 2009: 1157-1164
Parts in Books or Collections
- 2011
- [p1]Cristian Sminchisescu, Liefeng Bo, Catalin Ionescu, Atul Kanaujia:
Feature-Based Pose Estimation. Visual Analysis of Humans 2011: 225-251
Informal and Other Publications
- 2023
- [i8]João Carreira, Michael King, Viorica Patraucean, Dilara Gokay, Catalin Ionescu, Yi Yang, Daniel Zoran, Joseph Heyward, Carl Doersch, Yusuf Aytar, Dima Damen, Andrew Zisserman:
Learning from One Continuous Video Stream. CoRR abs/2312.00598 (2023) - 2022
- [i7]João Carreira, Skanda Koppula, Daniel Zoran, Adrià Recasens, Catalin Ionescu, Olivier J. Hénaff, Evan Shelhamer, Relja Arandjelovic, Matthew M. Botvinick, Oriol Vinyals, Karen Simonyan, Andrew Zisserman, Andrew Jaegle:
Hierarchical Perceiver. CoRR abs/2202.10890 (2022) - 2021
- [i6]Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira:
Perceiver IO: A General Architecture for Structured Inputs & Outputs. CoRR abs/2107.14795 (2021) - 2020
- [i5]Brendan O'Donoghue, Ian Osband, Catalin Ionescu:
Making Sense of Reinforcement Learning and Probabilistic Inference. CoRR abs/2001.00805 (2020) - 2019
- [i4]Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih:
Unsupervised Learning of Object Keypoints for Perception and Control. CoRR abs/1906.11883 (2019) - 2018
- [i3]David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih:
Unsupervised Control Through Non-Parametric Discriminative Rewards. CoRR abs/1811.11359 (2018) - 2016
- [i2]Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, Catalin Ionescu:
Using Fast Weights to Attend to the Recent Past. CoRR abs/1610.06258 (2016) - 2015
- [i1]Catalin Ionescu, Orestis Vantzos, Cristian Sminchisescu:
Training Deep Networks with Structured Layers by Matrix Backpropagation. CoRR abs/1509.07838 (2015)
Coauthor Index
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