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Computer Science

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44
Citations
22764
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7354
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Overview

Chen Sun is a researcher affiliated with Google in the United States, focusing on various areas within computer science and engineering. Their work spans key fields including computer vision, pattern recognition, artificial intelligence, automotive engineering, and control and systems engineering.

The main fields of study for Chen Sun encompass:

  • Computer Science
  • Engineering

Within these fields, their subfields of specialization include:

  • Computer Vision and Pattern Recognition
  • Automotive Engineering
  • Artificial Intelligence
  • Control and Systems Engineering
  • Building and Construction

The major research topics covered by Chen Sun in their publications involve:

  • Autonomous Vehicle Technology and Safety
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Anomaly Detection Techniques and Applications
  • Traffic Control and Management
  • Advanced Neural Network Applications
  • Safety Systems Engineering in Autonomy

Chen Sun has contributed numerous papers to several prominent publication venues. Their most frequent outlets are:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Intelligent Vehicles
  • IEEE Transactions on Systems Man and Cybernetics Systems
  • IEEE Intelligent Transportation Systems Magazine

Among recent publications, notable papers include:

  • What Makes for Good Views for Contrastive Learning? (2020), arXiv (Cornell University)
  • Attention Bottlenecks for Multimodal Fusion (2021), arXiv (Cornell University)
  • Multiview Transformers for Video Recognition (2022), 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • ViViT: A Video Vision Transformer (2021), 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Verification and Validation Methods for Decision-Making and Planning of Automated Vehicles: A Review (2022), IEEE Transactions on Intelligent Vehicles

The researcher has collaborated extensively with several frequent coauthors including:

  • Amir Khajepour
  • Dongpu Cao
  • Cordelia Schmid
  • Zejian Deng
  • Arsha Nagrani

Chen Sun's body of work reflects a focus on autonomy, machine learning applications, and safety in intelligent systems, contributing to both theoretical developments and applied technologies within these domains.

Best Publications

  • Speed/Accuracy Trade-Offs for Modern Convolutional Object Detectors

    Jonathan Huang;Vivek Rathod;Chen Sun;Menglong Zhu

  • Revisiting Unreasonable Effectiveness of Data in Deep Learning Era

    Chen Sun;Abhinav Shrivastava;Saurabh Singh;Abhinav Gupta

  • Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification

    Saining Xie;Chen Sun;Jonathan Huang;Zhuowen Tu

  • The iNaturalist Species Classification and Detection Dataset

    Grant Van Horn;Oisin Mac Aodha;Yang Song;Yin Cui

  • VideoBERT: A Joint Model for Video and Language Representation Learning

    Chen Sun;Austin Myers;Carl Vondrick;Kevin Murphy

  • AVA: A Video Dataset of Spatio-Temporally Localized Atomic Visual Actions

    Chunhui Gu;Chen Sun;David A. Ross;Carl Vondrick

  • VectorNet: Encoding HD Maps and Agent Dynamics From Vectorized Representation

    Jiyang Gao;Chen Sun;Hang Zhao;Yi Shen

  • TALL: Temporal Activity Localization via Language Query

    Jiyang Gao;Chen Sun;Zhenheng Yang;Ram Nevatia

  • What Makes for Good Views for Contrastive Learning

    Yonglong Tian;Chen Sun;Ben Poole;Dilip Krishnan

  • Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning

    Yin Cui;Yang Song;Chen Sun;Andrew Howard

  • Multi-modal Transformer for Video Retrieval

    Valentin Gabeur;Valentin Gabeur;Chen Sun;Karteek Alahari;Cordelia Schmid

  • TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals

    Jiyang Gao;Zhenheng Yang;Chen Sun;Kan Chen

  • DenseTNT: End-to-end Trajectory Prediction from Dense Goal Sets

    Junru Gu;Chen Sun;Hang Zhao

  • Multiview Transformers for Video Recognition

    Unknown

  • Composing Text and Image for Image Retrieval - an Empirical Odyssey

    Nam Vo;Lu Jiang;Chen Sun;Kevin Murphy

  • Learning Video Representations using Contrastive Bidirectional Transformer

    Chen Sun;Fabien Baradel;Kevin Murphy;Cordelia Schmid

  • Attention Bottlenecks for Multimodal Fusion

    Arsha Nagrani;Shan Yang;Anurag Arnab;Aren Jansen

  • Actor-Centric Relation Network

    Chen Sun;Abhinav Shrivastava;Carl Martin Vondrick;Kevin Murphy

  • Rethinking Spatiotemporal Feature Learning For Video Understanding.

    Saining Xie;Chen Sun;Jonathan Huang;Zhuowen Tu

  • TNT: Target-driveN Trajectory Prediction

    Hang Zhao;Jiyang Gao;Tian Lan;Chen Sun

  • Contrastive Bidirectional Transformer for Temporal Representation Learning

    Chen Sun;Fabien Baradel;Kevin Murphy;Cordelia Schmid

Frequent Co-Authors

Cordelia Schmid
Cordelia Schmid French Institute for Research in Computer Science and Automation - INRIA
Rahul Sukthankar
Rahul Sukthankar Google (United States)
Carl Vondrick
Carl Vondrick Columbia University
Abhinav Shrivastava
Abhinav Shrivastava University of Maryland, College Park
Chuang Gan
Chuang Gan University of Massachusetts Amherst
Jiajun Wu
Jiajun Wu Stanford University
Karteek Alahari
Karteek Alahari French Institute for Research in Computer Science and Automation - INRIA
Serge Belongie
Serge Belongie University of Copenhagen
Cees G. M. Snoek
Cees G. M. Snoek University of Amsterdam

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