Zhu, Yuke

Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations

Krishna, R., Zhu, Y., Groth, O., Johnson, J., Hata, K., Kravitz, J., Chen, S., Kalantidis, Y., Li, L.-J., Shamma, D. A., et al. (2017) · International Journal of Computer Vision

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 5,107

Target-driven visual navigation in indoor scenes using deep reinforcement learning

Zhu, Y., Mottaghi, R., Kolve, E., Lim, J. J., Gupta, A., Fei-Fei, L., & Farhadi, A. (2017) · 2017 IEEE International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 1,533

Scene Graph Generation by Iterative Message Passing

Xu, D., Zhu, Y., Choy, C. B., & Fei-Fei, L. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 1,271

Visual7W: Grounded Question Answering in Images

Zhu, Y., Groth, O., Bernstein, M., & Fei-Fei, L. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsVisual Attention and Saliency Detection

Cited by 794

AI2-THOR: An Interactive 3D Environment for Visual AI

Kolve, E., Mottaghi, R., Han, W., VanderBilt, E., Weihs, L., Herrasti, A., Deitke, M., Ehsani, K., Gordon, D., Zhu, Y., et al. (2017) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 578

Making Sense of Vision and Touch: Self-Supervised Learning of Multimodal Representations for Contact-Rich Tasks

Lee, M. A., Zhu, Y., Srinivasan, K., Shah, P., Savarese, S., Fei-Fei, L., Garg, A., & Bohg, J. (2019) · 2019 International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 349

MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Mandlekar, A., Nasiriany, S., Wen, B., Akinola, I., Narang, Y., Fan, L., Zhu, Y., & Fox, D. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 226

Voyager: An Open-Ended Embodied Agent with Large Language Models

Wang, G., Xie, Y., Jiang, Y., Mandlekar, A., Xiao, C., Zhu, Y., Fan, L., & Anandkumar, A. (2023) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 222

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration 0

O’Neill, A., Rehman, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., Mandlekar, A., Jain, A., et al. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 210

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Khazatsky, A., Pertsch, K., Nair, S., Balakrishna, A., Dasari, S., Karamcheti, S., Nasiriany, S., Srirama, M. K., Chen, L. Y., Ellis, K., et al. (2024) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 159

DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Khazatsky, A., Pertsch, K., Nair, S., Balakrishna, A., Dasari, S., Karamcheti, S., Nasiriany, S., Srirama, M., Chen, L., Ellis, K., et al. (2024) · Robotics: Science and Systems XX

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 159

Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles

Cui, J., Qiu, H., Chen, D., Stone, P., & Zhu, Y. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Autonomous Vehicle Technology and SafetyVehicular Ad Hoc Networks (VANETs)

Cited by 138

LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning

Liu, B., Zhu, Y., Gao, C., Feng, Y., Liu, Q., Zhu, Y., & Stone, P. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 135

LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning

Liu, B., Zhu, Y., Gao, C., Feng, Y., Liu, Q., Zhu, Y., & Stone, P. (2023) · Advances in Neural Information Processing Systems 36

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 135

ROBOTURK: A Crowdsourcing Platform for Robotic Skill Learning through Imitation

Mandlekar, A., Zhu, Y., Garg, A., Booher, J., Spero, M., Tung, A., Gao, J., Emmons, J., Gupta, A., Orbay, E., et al. (2018) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 134

Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations

Jiang, Z., Zhu, Y., Svetlik, M., Fang, K., & Zhu, Y. (2021) · arXiv

Robot Manipulation and Learning3D Shape Modeling and Analysis

Cited by 122

Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations

Jiang, Z., Zhu, Y., Svetlik, M., Fang, K., & Zhu, Y. (2021) · Robotics: Science and Systems XVII

Robot Manipulation and Learning3D Shape Modeling and Analysis

Cited by 122

Adversarially Robust Policy Learning: Active construction of physically-plausible perturbations

Mandlekar, A., Zhu, Y., Garg, A., Fei-Fei, L., & Savarese, S. (2017) · 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Adversarial Robustness in Machine LearningReinforcement Learning in Robotics

Cited by 116

Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Embodiment Collaboration, O'Neill, A., Rehman, A., Gupta, A., Maddukuri, A., Gupta, A., Padalkar, A., Lee, A., Pooley, A., Gupta, A., et al. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 111

VIMA: General Robot Manipulation with Multimodal Prompts

Jiang, Y., Gupta, A., Zhang, Z., Wang, G., Dou, Y., Chen, Y., Fei-Fei, L., Anandkumar, A., Zhu, Y., & Fan, L. (2022) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 95

Ditto: Building Digital Twins of Articulated Objects from Interaction

Jiang, Z., Hsu, C.-C., & Zhu, Y. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisRobot Manipulation and Learning

Cited by 92

Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks

Nasiriany, S., Liu, H., & Zhu, Y. (2022) · 2022 International Conference on Robotics and Automation (ICRA)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 91

MultiBench: Multiscale Benchmarks for Multimodal Representation Learning

Liang, P. P., Lyu, Y., Fan, X., Wu, Z., Cheng, Y., Wu, J., Chen, L., Wu, P., Lee, M. A., Zhu, Y., et al. (2021) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 85

MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge

Fan, L., Wang, G., Jiang, Y., Mandlekar, A., Yang, Y., Zhu, H., Tang, A., Huang, D.-A., Zhu, Y., & Anandkumar, A. (2022) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 72