Mingxing Tan

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 76

Top Topics

Occlusion Boundaries

Object Detection

Top Venues

Publications

Longlong Jing, Ruichi Yu, Xu Chen, Zhengli Zhao, Shiwei Sheng, Colin Graber, Qi Chen, Qinru Li, Shangxuan Wu, Han Deng, Sangjin Lee, Chris Sweeney, Qiurui He, Wei-Chih Hung, Tong He, Xingyi Zhou, Farshid Moussavi, Zijian Guo, Yin Zhou, Mingxing Tan, Weilong Yang, Congcong Li
STT: Stateful Tracking with Transformers for Autonomous Driving. CoRR (2024)
Zhaoqi Leng, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan
PVTransformer: Point-to-Voxel Transformer for Scalable 3D Object Detection. CoRR (2024)
Zhaoqi Leng, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan
PVTransformer: Point-to-Voxel Transformer for Scalable 3D Object Detection. ICRA (2024)
Kan Chen, Runzhou Ge, Hang Qiu, Rami Ai-Rfou, Charles R. Qi, Xuanyu Zhou, Zoey Yang, Scott Ettinger, Pei Sun, Zhaoqi Leng, Mustafa Baniodeh, Ivan Bogun, Weiyue Wang, Mingxing Tan, Dragomir Anguelov
WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting. ICRA (2024)
Longlong Jing, Ruichi Yu, Xu Chen, Zhengli Zhao, Shiwei Sheng, Colin Graber, Qi Chen, Qinru Li, Shangxuan Wu, Han Deng, Sangjin Lee, Chris Sweeney, Qiurui He, Wei-Chih Hung, Tong He, Xingyi Zhou, Farshid Moussavi, James Guo, Yin Zhou, Mingxing Tan, Weilong Yang, Congcong Li
STT: Stateful Tracking with Transformers for Autonomous Driving. ICRA (2024)
Kan Chen, Runzhou Ge, Hang Qiu, Rami Ai-Rfou, Charles R. Qi, Xuanyu Zhou, Zoey Yang, Scott Ettinger, Pei Sun, Zhaoqi Leng, Mustafa Mustafa, Ivan Bogun, Weiyue Wang, Mingxing Tan, Dragomir Anguelov
WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting. CoRR (2023)
Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan
Lidar Augment: Searching for Scalable 3D LiDAR Data Augmentations. ICRA (2023)
Sheng Li, Garrett Andersen, Tao Chen, Liqun Cheng, Julian Grady, Da Huang, Quoc V. Le, Andrew Li, Xin Li, Yang Li, Chen Liang, Yifeng Lu, Yun Ni, Ruoming Pang, Mingxing Tan, Martin Wicke, Gang Wu, Shengqi Zhu, Parthasarathy Ranganathan, Norman P. Jouppi
Hyperscale Hardware Optimized Neural Architecture Search. ASPLOS (3) (2023)
Hieu Pham, Zihang Dai, Golnaz Ghiasi, Kenji Kawaguchi, Hanxiao Liu, Adams Wei Yu, Jiahui Yu, Yi-Ting Chen, Minh-Thang Luong, Yonghui Wu, Mingxing Tan, Quoc V. Le
Combined scaling for zero-shot transfer learning. Neurocomputing 555 (2023)
Tong He, Pei Sun, Zhaoqi Leng, Chenxi Liu, Dragomir Anguelov, Mingxing Tan
LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection. IROS (2023)
Tong He, Pei Sun, Zhaoqi Leng, Chenxi Liu, Dragomir Anguelov, Mingxing Tan
LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection. CoRR (2023)
Reza Mahjourian, Jinkyu Kim, Yuning Chai, Mingxing Tan, Ben Sapp, Dragomir Anguelov
Occupancy Flow Fields for Motion Forecasting in Autonomous Driving. IEEE Robotics Autom. Lett. 7 (2) (2022)
Reza Mahjourian, Jinkyu Kim, Yuning Chai, Mingxing Tan, Benjamin Sapp, Dragomir Anguelov
Occupancy Flow Fields for Motion Forecasting in Autonomous Driving. CoRR (2022)
Yingwei Li, Adams Wei Yu, Tianjian Meng, Benjamin Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Bo Wu, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan L. Yuille, Mingxing Tan
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. CoRR (2022)
Yingwei Li, Adams Wei Yu, Tianjian Meng, Benjamin Caine, Jiquan Ngiam, Daiyi Peng, Junyang Shen, Yifeng Lu, Denny Zhou, Quoc V. Le, Alan L. Yuille, Mingxing Tan
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. CVPR (2022)
Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Jay Shi, Shuyang Cheng, Dragomir Anguelov
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. ICLR (2022)
Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov
PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. ECCV (31) (2022)
Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan
LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations. CoRR (2022)
Chenxi Liu, Zhaoqi Leng, Pei Sun, Shuyang Cheng, Charles R. Qi, Yin Zhou, Mingxing Tan, Dragomir Anguelov
LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds. ECCV (21) (2022)
Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Xiaojie Shi, Shuyang Cheng, Dragomir Anguelov
PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. CoRR (2022)
Chenxi Liu, Zhaoqi Leng, Pei Sun, Shuyang Cheng, Charles R. Qi, Yin Zhou, Mingxing Tan, Dragomir Anguelov
LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds. CoRR (2022)
Yanqi Zhou, Xuanyi Dong, Tianjian Meng, Mingxing Tan, Berkin Akin, Daiyi Peng, Amir Yazdanbakhsh, Da Huang, Ravi Narayanaswami, James Laudon
Towards the Co-design of Neural Networks and Accelerators. MLSys (2022)
Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, Dragomir Anguelov
SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds. ECCV (10) (2022)
Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, Dragomir Anguelov
SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds. CoRR (2022)
Tianjian Meng, Golnaz Ghiasi, Reza Mahjourian, Quoc V. Le, Mingxing Tan
Revisiting Multi-Scale Feature Fusion for Semantic Segmentation. CoRR (2022)
Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov
PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. CoRR (2022)
Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc V. Le, Yang You, Sameer Kumar
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. IPDPS Workshops (2021)
Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Yongzhe Wang, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. CVPR (2021)
Mingxing Tan, Quoc V. Le
EfficientNetV2: Smaller Models and Faster Training. CoRR (2021)
Mingxing Tan, Quoc V. Le
EfficientNetV2: Smaller Models and Faster Training. ICML (2021)
Xiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong
Robust and Accurate Object Detection via Adversarial Learning. CVPR (2021)
Yanqi Zhou, Xuanyi Dong, Berkin Akin, Mingxing Tan, Daiyi Peng, Tianjian Meng, Amir Yazdanbakhsh, Da Huang, Ravi Narayanaswami, James Laudon
Rethinking Co-design of Neural Architectures and Hardware Accelerators. CoRR (2021)
Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan L. Yuille, Cihang Xie
Shape-Texture Debiased Neural Network Training. ICLR (2021)
Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan
CoAtNet: Marrying Convolution and Attention for All Data Sizes. CoRR (2021)
Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi
Searching for Fast Model Families on Datacenter Accelerators. CVPR (2021)
Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi
Searching for Fast Model Families on Datacenter Accelerators. CoRR (2021)
Xiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong
Robust and Accurate Object Detection via Adversarial Learning. CoRR (2021)
Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan
CoAtNet: Marrying Convolution and Attention for All Data Sizes. NeurIPS (2021)
Hieu Pham, Zihang Dai, Golnaz Ghiasi, Hanxiao Liu, Adams Wei Yu, Minh-Thang Luong, Mingxing Tan, Quoc V. Le
Combined Scaling for Zero-shot Transfer Learning. CoRR (2021)
Dan Kondratyuk, Liangzhe Yuan, Yandong Li, Li Zhang, Mingxing Tan, Matthew Brown, Boqing Gong
MoViNets: Mobile Video Networks for Efficient Video Recognition. CVPR (2021)
Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh
Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention. AAAI (2021)
Daiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Hanxiao Liu, Gabriel Bender, Adam Kraft, Chen Liang, Quoc V. Le
PyGlove: Symbolic Programming for Automated Machine Learning. CoRR (2021)
Dan Kondratyuk, Liangzhe Yuan, Yandong Li, Li Zhang, Mingxing Tan, Matthew Brown, Boqing Gong
MoViNets: Mobile Video Networks for Efficient Video Recognition. CoRR (2021)
Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh
Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention. CoRR (2021)
Yunyang Xiong, Hanxiao Liu, Suyog Gupta, Berkin Akin, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Vikas Singh, Bo Chen
MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. CoRR (2020)
Michael S. Ryoo, A. J. Piergiovanni, Mingxing Tan, Anelia Angelova
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures. ICLR (2020)
Dan Kondratyuk, Mingxing Tan, Matthew Brown, Boqing Gong
When Ensembling Smaller Models is More Efficient than Single Large Models. CoRR (2020)
Cihang Xie, Mingxing Tan, Boqing Gong, Alan L. Yuille, Quoc V. Le
Smooth Adversarial Training. CoRR (2020)
Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song
Efficient Scale-Permuted Backbone with Learned Resource Distribution. ECCV (23) (2020)
Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan L. Yuille, Quoc V. Le
Adversarial Examples Improve Image Recognition. CVPR (2020)
Daiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Gabriel Bender, Hanxiao Liu, Adam Kraft, Chen Liang, Quoc Le
PyGlove: Symbolic Programming for Automated Machine Learning. NeurIPS (2020)
Xuanyi Dong, Mingxing Tan, Adams Wei Yu, Daiyi Peng, Bogdan Gabrys, Quoc V. Le
AutoHAS: Differentiable Hyper-parameter and Architecture Search. CoRR (2020)
Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. ICML (2020)
Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang
Search to Distill: Pearls Are Everywhere but Not the Eyes. CVPR (2020)
Arissa Wongpanich, Hieu Pham, James Demmel, Mingxing Tan, Quoc V. Le, Yang You, Sameer Kumar
Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. CoRR (2020)
Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan L. Yuille, Cihang Xie
Shape-Texture Debiased Neural Network Training. CoRR (2020)
Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas S. Huang, Xiaodan Song, Ruoming Pang, Quoc V. Le
BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models. CoRR (2020)
Jiahui Yu, Pengchong Jin, Hanxiao Liu, Gabriel Bender, Pieter-Jan Kindermans, Mingxing Tan, Thomas S. Huang, Xiaodan Song, Ruoming Pang, Quoc Le
BigNAS: Scaling up Neural Architecture Search with Big Single-Stage Models. ECCV (7) (2020)
Mingxing Tan, Ruoming Pang, Quoc V. Le
EfficientDet: Scalable and Efficient Object Detection. CVPR (2020)
Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song
Efficient Scale-Permuted Backbone with Learned Resource Distribution. CoRR (2020)
Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans
Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. CoRR (2020)
Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V. Le, Xiaodan Song
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization. CVPR (2020)
Andrew Howard, Mark Sandler, Grace Chu, Liang-Chieh Chen, Bo Chen, Mingxing Tan, Weijun Wang, Yukun Zhu, Ruoming Pang, Vijay Vasudevan, Quoc V. Le, Hartwig Adam
Searching for MobileNetV3. CoRR (2019)
Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan L. Yuille, Quoc V. Le
Adversarial Examples Improve Image Recognition. CoRR (2019)
Mingxing Tan, Quoc V. Le
MixConv: Mixed Depthwise Convolutional Kernels. BMVC (2019)
Mingxing Tan, Quoc V. Le
MixConv: Mixed Depthwise Convolutional Kernels. CoRR (2019)
Michael S. Ryoo, A. J. Piergiovanni, Mingxing Tan, Anelia Angelova
AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures. CoRR (2019)
Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang
Search to Distill: Pearls are Everywhere but not the Eyes. CoRR (2019)
Andrew Howard, Ruoming Pang, Hartwig Adam, Quoc V. Le, Mark Sandler, Bo Chen, Weijun Wang, Liang-Chieh Chen, Mingxing Tan, Grace Chu, Vijay Vasudevan, Yukun Zhu
Searching for MobileNetV3. ICCV (2019)
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le
MnasNet: Platform-Aware Neural Architecture Search for Mobile. CVPR (2019)
Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Golnaz Ghiasi, Mingxing Tan, Yin Cui, Quoc V. Le, Xiaodan Song
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization. CoRR (2019)
Mingxing Tan, Quoc V. Le
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. ICML (2019)
Mingxing Tan, Quoc V. Le
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. CoRR (2019)
Mingxing Tan, Ruoming Pang, Quoc V. Le
EfficientDet: Scalable and Efficient Object Detection. CoRR (2019)
Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Quoc V. Le
MnasNet: Platform-Aware Neural Architecture Search for Mobile. CoRR (2018)
Gai Liu, Mingxing Tan, Steve Dai, Ritchie Zhao, Zhiru Zhang
Architecture and Synthesis for Area-Efficient Pipelining of Irregular Loop Nests. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 36 (11) (2017)
Mingkai Huang, Dan He, Xianhua Liu, Mingxing Tan, Xu Cheng
An Energy-Efficient Branch Prediction with Grouped Global History. ICPP (2015)
Mingxing Tan, Gai Liu, Ritchie Zhao, Steve Dai, Zhiru Zhang
ElasticFlow: A Complexity-Effective Approach for Pipelining Irregular Loop Nests. ICCAD (2015)
Ritchie Zhao, Mingxing Tan, Steve Dai, Zhiru Zhang
Area-efficient pipelining for FPGA-targeted high-level synthesis. DAC (2015)
Mingxing Tan, Steve Dai, Udit Gupta, Zhiru Zhang
Mapping-Aware Constrained Scheduling for LUT-Based FPGAs. FPGA (2015)
Shreesha Srinath, Berkin Ilbeyi, Mingxing Tan, Gai Liu, Zhiru Zhang, Christopher Batten
Architectural Specialization for Inter-Iteration Loop Dependence Patterns. MICRO (2014)
Gai Liu, Ye Tao, Mingxing Tan, Zhiru Zhang
CASA: correlation-aware speculative adders. ISLPED (2014)
Mingxing Tan, Bin Liu, Steve Dai, Zhiru Zhang
Multithreaded pipeline synthesis for data-parallel kernels. ICCAD (2014)
Steve Dai, Mingxing Tan, Kecheng Hao, Zhiru Zhang
Flushing-Enabled Loop Pipelining for High-Level Synthesis. DAC (2014)
Mingxing Tan, Xianhua Liu, Tong Tong, Xu Cheng
CVP: an energy-efficient indirect branch prediction with compiler-guided value pattern. ICS (2012)
Mingxing Tan, Xianhua Liu, Zichao Xie, Dong Tong, Xu Cheng
Energy-efficient branch prediction with Compiler-guided History Stack. DATE (2012)
Jiyu Zhang, Zhiru Zhang, Sheng Zhou, Mingxing Tan, Xianhua Liu, Xu Cheng, Jason Cong
Bit-level optimization for high-level synthesis and FPGA-based acceleration. FPGA (2010)