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Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout

Oct 14, 2020
Zhao Chen, Jiquan Ngiam, Yanping Huang, Thang Luong, Henrik Kretzschmar, Yuning Chai, Dragomir Anguelov

* Conference on Neural Information Processing Systems (NeurIPS) 2020 

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TNT: Target-driveN Trajectory Prediction

Aug 21, 2020
Hang Zhao, Jiyang Gao, Tian Lan, Chen Sun, Benjamin Sapp, Balakrishnan Varadarajan, Yue Shen, Yi Shen, Yuning Chai, Cordelia Schmid, Congcong Li, Dragomir Anguelov


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SoDA: Multi-Object Tracking with Soft Data Association

Aug 19, 2020
Wei-Chih Hung, Henrik Kretzschmar, Tsung-Yi Lin, Yuning Chai, Ruichi Yu, Ming-Hsuan Yang, Dragomir Anguelov


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Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection

May 20, 2020
Alex Bewley, Pei Sun, Thomas Mensink, Dragomir Anguelov, Cristian Sminchisescu

* 20 pages 

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VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation

May 08, 2020
Jiyang Gao, Chen Sun, Hang Zhao, Yi Shen, Dragomir Anguelov, Congcong Li, Cordelia Schmid

* CVPR 2020 

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STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction

May 08, 2020
Zhishuai Zhang, Jiyang Gao, Junhua Mao, Yukai Liu, Dragomir Anguelov, Congcong Li

* CVPR 2020 

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SurfelGAN: Synthesizing Realistic Sensor Data for Autonomous Driving

May 08, 2020
Zhenpei Yang, Yuning Chai, Dragomir Anguelov, Yin Zhou, Pei Sun, Dumitru Erhan, Sean Rafferty, Henrik Kretzschmar

* CVPR 2020 

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Improving 3D Object Detection through Progressive Population Based Augmentation

Apr 02, 2020
Shuyang Cheng, Zhaoqi Leng, Ekin Dogus Cubuk, Barret Zoph, Chunyan Bai, Jiquan Ngiam, Yang Song, Benjamin Caine, Vijay Vasudevan, Congcong Li, Quoc V. Le, Jonathon Shlens, Dragomir Anguelov


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Scalability in Perception for Autonomous Driving: Waymo Open Dataset

Dec 18, 2019
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jonathon Shlens, Zhifeng Chen, Dragomir Anguelov


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Scalability in Perception for Autonomous Driving: An Open Dataset Benchmark

Dec 11, 2019
Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han, Jiquan Ngiam, Hang Zhao, Aleksei Timofeev, Scott Ettinger, Maxim Krivokon, Amy Gao, Aditya Joshi, Yu Zhang, Jon Shlens, Zhifeng Chen, Dragomir Anguelov


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End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Clouds

Oct 23, 2019
Yin Zhou, Pei Sun, Yu Zhang, Dragomir Anguelov, Jiyang Gao, Tom Ouyang, James Guo, Jiquan Ngiam, Vijay Vasudevan

* CoRL2019 

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MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Prediction

Oct 12, 2019
Yuning Chai, Benjamin Sapp, Mayank Bansal, Dragomir Anguelov

* Appears in CoRL 2019 

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PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation

Aug 25, 2018
Danfei Xu, Dragomir Anguelov, Ashesh Jain

* CVPR 2018 

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3D Bounding Box Estimation Using Deep Learning and Geometry

Apr 10, 2017
Arsalan Mousavian, Dragomir Anguelov, John Flynn, Jana Kosecka

* To appear in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 

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SSD: Single Shot MultiBox Detector

Dec 29, 2016
Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang Fu, Alexander C. Berg

* ECCV 2016 

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Self-taught Object Localization with Deep Networks

Feb 02, 2016
Loris Bazzani, Alessandro Bergamo, Dragomir Anguelov, Lorenzo Torresani

* WACV 2016 

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Scalable, High-Quality Object Detection

Dec 09, 2015
Christian Szegedy, Scott Reed, Dumitru Erhan, Dragomir Anguelov, Sergey Ioffe


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Training Deep Neural Networks on Noisy Labels with Bootstrapping

Apr 15, 2015
Scott Reed, Honglak Lee, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Andrew Rabinovich


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Self-informed neural network structure learning

Apr 13, 2015
David Warde-Farley, Andrew Rabinovich, Dragomir Anguelov

* Updated with accepted workshop contribution header 

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Going Deeper with Convolutions

Sep 17, 2014
Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich


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Scalable Object Detection using Deep Neural Networks

Dec 08, 2013
Dumitru Erhan, Christian Szegedy, Alexander Toshev, Dragomir Anguelov


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A General Algorithm for Approximate Inference and its Application to Hybrid Bayes Nets

Jan 23, 2013
Daphne Koller, Uri Lerner, Dragomir Anguelov

* Appears in Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (UAI1999) 

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Learning Hierarchical Object Maps Of Non-Stationary Environments with mobile robots

Dec 12, 2012
Dragomir Anguelov, Rahul Biswas, Daphne Koller, Benson Limketkai, Sebastian Thrun

* Appears in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002) 

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Recovering Articulated Object Models from 3D Range Data

Jul 11, 2012
Dragomir Anguelov, Daphne Koller, Hoi-Cheung Pang, Praveen Srinivasan, Sebastian Thrun

* Appears in Proceedings of the Twentieth Conference on Uncertainty in Artificial Intelligence (UAI2004) 

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