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To promote better performance-bandwidth trade-off for multi-agent perception, we propose a novel distilled collaboration graph (DiscoGraph) to model trainable, pose-aware, and adaptive collaboration among agents.
Multiagent systems: Algorithmic, game-theoretic, and logical foundations
Yoav Shoham and Kevin Leyton-Brown · 2008
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Stacked convolutional auto-encoders for hierarchical feature extraction
Jonathan Masci, Ueli Meier, Dan Cireşan, and Jürgen Schmidhuber · 2011
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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Recent development and applications of sumo-simulation of urban mobility
Daniel Krajzewicz, Jakob Erdmann, Michael Behrisch, and Laura Bieker · 2012
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Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean · 2015
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Fitnets: Hints for thin deep nets
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio · 2015
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Learning to communicate with deep multi-agent reinforcement learning
Jakob N. Foerster, Yannis M. Assael, N. D. Freitas, and S. Whiteson · 2016
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Learning multiagent communication with backpropagation
Sainbayar Sukhbaatar, Arthur D. Szlam, and Rob Fergus · 2016
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CARLA: An open urban driving simulator
Alexey Dosovitskiy, German Ros, Felipe Codevilla, Antonio Lopez, and Vladlen Koltun · 2017
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Vain: Attentional multi-agent predictive modeling
Yedid Hoshen · 2017
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Large scale distributed neural network training through online distillation
Rohan Anil, Gabriel Pereyra, Alexandre Passos, Robert Ormandi, George E Dahl, and Geoffrey E Hinton · 2018
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Distributed perception by collaborative robots
Ramyad Hadidi, Jiashen Cao, Matthew Woodward, Michael S Ryoo, and Hyesoon Kim · 2018
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Learning attentional communication for multi-agent cooperation
Jiechuan Jiang and Zongqing Lu · 2018
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Towards collaborative perception for automated vehicles in heterogeneous traffic
Saifullah Khan, Franz Andert, Nicolai Wojke, Julian Schindler, Alejandro Correa, and Anton Wijbenga · 2018
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Large-scale point cloud semantic segmentation with superpoint graphs
Loic Landrieu and Martin Simonovsky · 2018
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Fast and furious: Real time end-to-end 3d detection, tracking and motion forecasting with a single convolutional net
Wenjie Luo, Bin Yang, and Raquel Urtasun · 2018
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Learning when to communicate at scale in multiagent cooperative and competitive tasks
Amanpreet Singh, Tushar Jain, and Sainbayar Sukhbaatar · 2018
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Voxelnet: End-to-end learning for point cloud based 3d object detection
Yin Zhou and Oncel Tuzel · 2018
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When2com: multi-agent perception via communication graph grouping
Yen-Cheng Liu, Junjiao Tian, Nathaniel Glaser, and Zsolt Kira · 2020
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Who2com: Collaborative perception via learnable handshake communication
Yen-Cheng Liu, Junjiao Tian, Chih-Yao Ma, Nathan Glaser, Chia-Wen Kuo, and Zsolt Kira · 2020
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From points to parts: 3d object detection from point cloud with part-aware and part-aggregation network
Shaoshuai Shi, Zhe Wang, Jianping Shi, Xiaogang Wang, and Hongsheng Li · 2020
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Point-gnn: Graph neural network for 3d object detection in a point cloud
Weijing Shi and Raj Rajkumar · 2020
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Learning to communicate and correct pose errors
Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, and Raquel Urtasun · 2020
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V2vnet: Vehicle-to-vehicle communication for joint perception and prediction
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Qi Chen, Sihai Tang, Qing Yang, and Song Fu · 2019
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Tarmac: Targeted multi-agent communication
Abhishek Das, Théophile Gervet, Joshua Romoff, Dhruv Batra, Devi Parikh, Mike Rabbat, and Joelle Pineau · 2019
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Structured knowledge distillation for semantic segmentation
Yifan Liu, Ke Chen, Chris Liu, Zengchang Qin, Zhenbo Luo, and Jingdong Wang · 2019
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Pointrcnn: 3d object proposal generation and detection from point cloud
Shaoshuai Shi, Xiaogang Wang, and Hongsheng Li · 2019
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nuscenes: A multimodal dataset for autonomous driving
Holger Caesar, Varun Bankiti, Alex H Lang, Sourabh Vora, Venice Erin Liong, Qiang Xu, Anush Krishnan, Yu Pan, Giancarlo Baldan, and Oscar Beijbom · 2020
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Uncertainty-aware multi-shot knowledge distillation for image-based object re-identification
Xin Jin, Cuiling Lan, Wenjun Zeng, and Zhibo Chen · 2020
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Deep learning for generic object detection: A survey
Li Liu, Wanli Ouyang, Xiaogang Wang, Paul Fieguth, Jie Chen, Xinwang Liu, and Matti Pietikäinen · 2020
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Tsun-Hsuan Wang, Sivabalan Manivasagam, Ming Liang, Bin Yang, Wenyuan Zeng, and Raquel Urtasun · 2020
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Multi-frame to single-frame: Knowledge distillation for 3d object detection
Yue Wang, Alireza Fathi, Jiajun Wu, Thomas Funkhouser, and Justin Solomon · 2020
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Collaborative semantic perception and relative localization based on map matching
Yufeng Yue, Chunyang Zhao, Mingxing Wen, Zhenyu Wu, and Danwei Wang · 2020
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3d point cloud processing and learning for autonomous driving: Impacting map creation, localization, and perception
Siheng Chen, Baoan Liu, Chen Feng, Carlos Vallespi-Gonzalez, and Carl K. Wellington · 2021
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Fooling lidar perception via adversarial trajectory perturbation
Yiming Li, Congcong Wen, Felix Juefei-Xu, and Chen Feng · 2021
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Deep learning for visual tracking: A comprehensive survey
Seyed Mojtaba Marvasti-Zadeh, Li Cheng, Hossein Ghanei-Yakhdan, and Shohreh Kasaei · 2021
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Image segmentation using deep learning: A survey
Shervin Minaee, Yuri Boykov, F. Porikli, A. Plaza, N. Kehtarnavaz, and Demetri Terzopoulos · 2021
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