Song, Shuran

ShapeNet: An Information-Rich 3D Model Repository

Chang, A. X., Funkhouser, T., Guibas, L., Hanrahan, P., Huang, Q., Li, Z., Savarese, S., Savva, M., Song, S., Su, H., et al. (2015) · arXiv

3D Shape Modeling and AnalysisImage Processing and 3D Reconstruction

Cited by 2,330

SUN RGB-D: A RGB-D scene understanding benchmark suite

Song, S., Lichtenberg, S. P., & Xiao, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Vision and Imaging

Cited by 1,943

Matterport3D: Learning from RGB-D Data in Indoor Environments

Chang, A., Dai, A., Funkhouser, T., Halber, M., Niebner, M., Savva, M., Song, S., Zeng, A., & Zhang, Y. (2017) · 2017 International Conference on 3D Vision (3DV)

3D Surveying and Cultural Heritage3D Shape Modeling and Analysis

Cited by 1,858

Diffusion policy: Visuomotor policy learning via action diffusion

Chi, C., Xu, Z., Feng, S., Cousineau, E., Du, Y., Burchfiel, B., Tedrake, R., & Song, S. (2025) · The International Journal of Robotics Research

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 613

Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning

Zeng, A., Song, S., Welker, S., Lee, J., Rodriguez, A., & Funkhouser, T. (2018) · 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 606

Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Chi, C., Feng, S., Du, Y., Xu, Z., Cousineau, E., Burchfiel, B., & Song, S. (2023) · Robotics: Science and Systems XIX

Reinforcement Learning in RoboticsMotor Control and Adaptation

Cited by 530

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

Category-Level Articulated Object Pose Estimation

Li, X., Wang, H., Yi, L., Guibas, L. J., Abbott, A. L., & Song, S. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Robot Manipulation and Learning3D Shape Modeling and Analysis

Cited by 196

Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning

NVIDIA, :, Azzolini, A., Bai, J., Brandon, H., Cao, J., Chattopadhyay, P., Chen, H., Chu, J., Cui, Y., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 187

Grasping in the Wild: Learning 6DoF Closed-Loop Grasping From Low-Cost Demonstrations

Song, S., Zeng, A., Lee, J., & Funkhouser, T. (2020) · IEEE Robotics and Automation Letters

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 185

Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots

Chi, C., Xu, Z., Pan, C., Cousineau, E., Burchfiel, B., Feng, S., Tedrake, R., & Song, S. (2024) · Robotics: Science and Systems XX

Robot Manipulation and LearningSocial Robot Interaction and HRI

Cited by 183

RoCo: Dialectic Multi-Robot Collaboration with Large Language Models

Mandi, Z., Jain, S., & Song, S. (2023) · arXiv

Robot Manipulation and LearningAI-based Problem Solving and Planning

Cited by 180

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

Sim2Real in Robotics and Automation: Applications and Challenges

Hofer, S., Bekris, K., Handa, A., Gamboa, J. C., Mozifian, M., Golemo, F., Atkeson, C., Fox, D., Goldberg, K., Leonard, J., et al. (2021) · IEEE Transactions on Automation Science and Engineering

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 154

DataComp: In search of the next generation of multimodal datasets

Gadre, S. Y., Ilharco, G., Fang, A., Hayase, J., Smyrnis, G., Nguyen, T., Marten, R., Wortsman, M., Ghosh, D., Zhang, J., et al. (2023) · Advances in Neural Information Processing Systems 36

Multimodal Machine Learning ApplicationsImage Retrieval and Classification Techniques

Cited by 120

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

FlingBot: The Unreasonable Effectiveness of Dynamic Manipulation for Cloth Unfolding

Ha, H., & Song, S. (2021) · arXiv

Robot Manipulation and LearningSoft Robotics and Applications

Cited by 93

What are the important technologies for bin picking? Technology analysis of robots in competitions based on a set of performance metrics

Fujita, M., Domae, Y., Noda, A., Garcia Ricardez, G. A., Nagatani, T., Zeng, A., Song, S., Rodriguez, A., Causo, A., Chen, I. M., et al. (2019) · Advanced Robotics

Robot Manipulation and LearningAdvanced Manufacturing and Logistics Optimization

Cited by 78

DextAIRity: Deformable Manipulation Can be a Breeze

Xu, Z., Chi, C., Burchfiel, B., Cousineau, E., Feng, S., & Song, S. (2022) · Robotics: Science and Systems XVIII

Robot Manipulation and LearningSoft Robotics and Applications

Cited by 45

Scaling Up and Distilling Down: Language-Guided Robot Skill Acquisition

Ha, H., Florence, P., & Song, S. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 24

CACTI: A Framework for Scalable Multi-Task Multi-Scene Visual Imitation Learning

Mandi, Z., Bharadhwaj, H., Moens, V., Song, S., Rajeswaran, A., & Kumar, V. (2022) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 19

Bag All You Need: Learning a Generalizable Bagging Strategy for Heterogeneous Objects

Bahety, A., Jain, S., Ha, H., Hager, N., Burchfiel, B., Cousineau, E., Feng, S., & Song, S. (2023) · 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 15

Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Chi, C., Xu, Z., Feng, S., Cousineau, E., Du, Y., Burchfiel, B., Tedrake, R., & Song, S. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 12