Dinesh Jayaraman

According to our database, Dinesh Jayaraman authored at least 79 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Eurekaverse: Environment Curriculum Generation via Large Language Models.

William Liang, Sam Wang, Hung-Ju Wang, Osbert Bastani, Dinesh Jayaraman, Yecheng Jason Ma

CoRR, 2024

Task-Oriented Hierarchical Object Decomposition for Visuomotor Control.

Jianing Qian, Yunshuang Li, Bernadette Bucher, Dinesh Jayaraman

CoRR, 2024

Learning to Achieve Goals with Belief State Transformers.

Edward S. Hu, Kwangjun Ahn, Qinghua Liu, Haoran Xu, Manan Tomar, Ada Langford, Dinesh Jayaraman, Alex Lamb, John Langford

CoRR, 2024

Articulate-Anything: Automatic Modeling of Articulated Objects via a Vision-Language Foundation Model.

Long Le, Jason Xie, William Liang, Hung-Ju Wang, Yue Yang, Yecheng Jason Ma, Kyle Vedder, Arjun Krishna, Dinesh Jayaraman, Eric Eaton

CoRR, 2024

Leveraging Symmetry to Accelerate Learning of Trajectory Tracking Controllers for Free-Flying Robotic Systems.

Jake Welde, Nishanth Rao, Pratik Kunapuli, Dinesh Jayaraman, Vijay Kumar

CoRR, 2024

DrEureka: Language Model Guided Sim-To-Real Transfer.

Yecheng Jason Ma, William Liang, Hung-Ju Wang, Sam Wang, Yuke Zhu, Linxi Fan, Osbert Bastani, Dinesh Jayaraman

CoRR, 2024

Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models.

Junyao Shi, Jianing Qian, Yecheng Jason Ma, Dinesh Jayaraman

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Recasting Generic Pretrained Vision Transformers As Object-Centric Scene Encoders For Manipulation Policies.

Jianing Qian, Anastasios Panagopoulos, Dinesh Jayaraman

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

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

Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Long-HOT: A Modular Hierarchical Approach for Long-Horizon Object Transport.

Sriram Narayanan, Dinesh Jayaraman, Manmohan Chandraker

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Universal Visual Decomposer: Long-Horizon Manipulation Made Easy.

Zichen Zhang, Yunshuang Li, Osbert Bastani, Abhishek Gupta, Dinesh Jayaraman, Yecheng Jason Ma, Luca Weihs

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Can Transformers Capture Spatial Relations between Objects?

Chuan Wen, Dinesh Jayaraman, Yang Gao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

ZeroFlow: Scalable Scene Flow via Distillation.

Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Memory-Consistent Neural Networks for Imitation Learning.

Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, James Weimer, Insup Lee

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Eureka: Human-Level Reward Design via Coding Large Language Models.

Yecheng Jason Ma, William Liang, Guanzhi Wang, De-An Huang, Osbert Bastani, Dinesh Jayaraman, Yuke Zhu, Linxi Fan, Anima Anandkumar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Privileged Sensing Scaffolds Reinforcement Learning.

Edward S. Hu, James Springer, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

TLControl: Trajectory and Language Control for Human Motion Synthesis.

Weilin Wan, Zhiyang Dou, Taku Komura, Wenping Wang, Dinesh Jayaraman, Lingjie Liu

Proceedings of the Computer Vision - ECCV 2024, 2024

Dynamic Grasping with a Learned Meta-Controller.

Yinsen Jia, Jingxi Xu, Dinesh Jayaraman, Shuran Song

Proceedings of the 20th IEEE International Conference on Automation Science and Engineering, 2024

2023

DiffusionPhase: Motion Diffusion in Frequency Domain.

Weilin Wan, Yiming Huang, Shutong Wu, Taku Komura, Wenping Wang, Dinesh Jayaraman, Lingjie Liu

CoRR, 2023

LIV: Language-Image Representations and Rewards for Robotic Control.

Yecheng Jason Ma, William Liang, Vaidehi Som, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman

CoRR, 2023

TOM: Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching.

Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman

CoRR, 2023

ZeroFlow: Fast Zero Label Scene Flow via Distillation.

Kyle Vedder, Neehar Peri, Nathaniel Chodosh, Ishan Khatri, Eric Eaton, Dinesh Jayaraman, Yang Liu, Deva Ramanan, James Hays

CoRR, 2023

Learning a Meta-Controller for Dynamic Grasping.

Yinsen Jia, Jingxi Xu, Dinesh Jayaraman, Shuran Song

CoRR, 2023

Learning Policy-Aware Models for Model-Based Reinforcement Learning via Transition Occupancy Matching.

Yecheng Jason Ma, Kausik Sivakumar, Jason Yan, Osbert Bastani, Dinesh Jayaraman

Proceedings of the Learning for Dynamics and Control Conference, 2023

LIV: Language-Image Representations and Rewards for Robotic Control.

Yecheng Jason Ma, Vikash Kumar, Amy Zhang, Osbert Bastani, Dinesh Jayaraman

Proceedings of the International Conference on Machine Learning, 2023

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training.

Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman, Osbert Bastani, Vikash Kumar, Amy Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Planning Goals for Exploration.

Edward S. Hu, Richard Chang, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Im2Contact: Vision-Based Contact Localization Without Touch or Force Sensing.

Leon Kim, Yunshuang Li, Michael Posa, Dinesh Jayaraman

Proceedings of the Conference on Robot Learning, 2023

Prospective Learning: Principled Extrapolation to the Future.

Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael L. Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Vision-based Perimeter Defense via Multiview Pose Estimation.

Elijah S. Lee, Giuseppe Loianno, Dinesh Jayaraman, Vijay Kumar

CoRR, 2022

How Far I'll Go: Offline Goal-Conditioned Reinforcement Learning via f-Advantage Regression.

Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani

CoRR, 2022

SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching.

Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani

CoRR, 2022

Prospective Learning: Back to the Future.

Joshua T. Vogelstein, Timothy D. Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael L. Platt, Lyle H. Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang

CoRR, 2022

Offline Goal-Conditioned Reinforcement Learning via $f$-Advantage Regression.

Yecheng Jason Ma, Jason Yan, Dinesh Jayaraman, Osbert Bastani

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming.

Chuan Wen, Jianing Qian, Jierui Lin, Jiaye Teng, Dinesh Jayaraman, Yang Gao

Proceedings of the International Conference on Machine Learning, 2022

Versatile Offline Imitation from Observations and Examples via Regularized State-Occupancy Matching.

Yecheng Jason Ma, Andrew Shen, Dinesh Jayaraman, Osbert Bastani

Proceedings of the International Conference on Machine Learning, 2022

Know Thyself: Transferable Visual Control Policies Through Robot-Awareness.

Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman

Proceedings of the Tenth International Conference on Learning Representations, 2022

Discovering Deformable Keypoint Pyramids.

Jianing Qian, Anastasios Panagopoulos, Dinesh Jayaraman

Proceedings of the Computer Vision - ECCV 2022, 2022

Training Robots to Evaluate Robots: Example-Based Interactive Reward Functions for Policy Learning.

Kun Huang, Edward S. Hu, Dinesh Jayaraman

Proceedings of the Conference on Robot Learning, 2022

Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning.

Yecheng Jason Ma, Andrew Shen, Osbert Bastani, Dinesh Jayaraman

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

An Exploration of Embodied Visual Exploration.

Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman

Int. J. Comput. Vis., 2021

Know Thyself: Transferable Visuomotor Control Through Robot-Awareness.

Edward S. Hu, Kun Huang, Oleh Rybkin, Dinesh Jayaraman

CoRR, 2021

Conservative Offline Distributional Reinforcement Learning.

Yecheng Jason Ma, Dinesh Jayaraman, Osbert Bastani

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?

Jingxi Xu, Bruce D. Lee, Nikolai Matni, Dinesh Jayaraman

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Keyframe-Focused Visual Imitation Learning.

Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman

Proceedings of the 38th International Conference on Machine Learning, 2021

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments.

Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

Proceedings of the 9th International Conference on Learning Representations, 2021

Likelihood-Based Diverse Sampling for Trajectory Forecasting.

Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Probabilistic Modeling for Human Mesh Recovery.

Nikos Kolotouros, Georgios Pavlakos, Dinesh Jayaraman, Kostas Daniilidis

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Morphology-Agnostic Visual Robotic Control.

Brian H. Yang, Dinesh Jayaraman, Glen Berseth, Alexei A. Efros, Sergey Levine

IEEE Robotics Autom. Lett., 2020

DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor With Application to In-Hand Manipulation.

Mike Lambeta, Po-Wei Chou, Stephen Tian, Brian H. Yang, Benjamin Maloon, Victoria Rose Most, Dave Stroud, Raymond Santos, Ahmad Byagowi, Gregg Kammerer, Dinesh Jayaraman, Roberto Calandra

IEEE Robotics Autom. Lett., 2020

Diverse Sampling for Normalizing Flow Based Trajectory Forecasting.

Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, Osbert Bastani

CoRR, 2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.

Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

CoRR, 2020

Fighting Copycat Agents in Behavioral Cloning from Observation Histories.

Chuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, Yang Gao

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.

Karl Pertsch, Oleh Rybkin, Frederik Ebert, Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings.

Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman

Proceedings of the 37th International Conference on Machine Learning, 2020

Model-Based Inverse Reinforcement Learning from Visual Demonstrations.

Neha Das, Sarah Bechtle, Todor Davchev, Dinesh Jayaraman, Akshara Rai, Franziska Meier

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Emergence of exploratory look-around behaviors through active observation completion.

Santhosh K. Ramakrishnan, Dinesh Jayaraman, Kristen Grauman

Sci. Robotics, 2019

End-to-End Policy Learning for Active Visual Categorization.

Dinesh Jayaraman, Kristen Grauman

IEEE Trans. Pattern Anal. Mach. Intell., 2019

SMiRL: Surprise Minimizing RL in Dynamic Environments.

Glen Berseth, Daniel Geng, Coline Devin, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

CoRR, 2019

REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning.

Brian H. Yang, Jesse Zhang, Vitchyr Pong, Sergey Levine, Dinesh Jayaraman

CoRR, 2019

Causal Confusion in Imitation Learning.

Pim de Haan, Dinesh Jayaraman, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

REPLAB: A Reproducible Low-Cost Arm Benchmark for Robotic Learning.

Brian H. Yang, Dinesh Jayaraman, Jesse Zhang, Sergey Levine

Proceedings of the International Conference on Robotics and Automation, 2019

Manipulation by Feel: Touch-Based Control with Deep Predictive Models.

Stephen Tian, Frederik Ebert, Dinesh Jayaraman, Mayur Mudigonda, Chelsea Finn, Roberto Calandra, Sergey Levine

Proceedings of the International Conference on Robotics and Automation, 2019

Time-Agnostic Prediction: Predicting Predictable Video Frames.

Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros, Sergey Levine

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch.

Roberto Calandra, Andrew Owens, Dinesh Jayaraman, Justin Lin, Wenzhen Yuan, Jitendra Malik, Edward H. Adelson, Sergey Levine

IEEE Robotics Autom. Lett., 2018

ShapeCodes: Self-supervised Feature Learning by Lifting Views to Viewgrids.

Dinesh Jayaraman, Ruohan Gao, Kristen Grauman

Proceedings of the Computer Vision - ECCV 2018, 2018

Learning to Look Around: Intelligently Exploring Unseen Environments for Unknown Tasks.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Learning Image Representations Tied to Egomotion from Unlabeled Video.

Dinesh Jayaraman, Kristen Grauman

Int. J. Comput. Vis., 2017

Learning to look around.

Dinesh Jayaraman, Kristen Grauman

CoRR, 2017

Unsupervised learning through one-shot image-based shape reconstruction.

Dinesh Jayaraman, Ruohan Gao, Kristen Grauman

CoRR, 2017

Pano2Vid: Automatic Cinematography for Watching 360° Videos.

Yu-Chuan Su, Dinesh Jayaraman, Kristen Grauman

Proceedings of the 6th Workshop on Intelligent Cinematography and Editing, 2017

2016

Look-Ahead Before You Leap: End-to-End Active Recognition by Forecasting the Effect of Motion.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the Computer Vision - ECCV 2016, 2016

Slow and Steady Feature Analysis: Higher Order Temporal Coherence in Video.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

Object-Centric Representation Learning from Unlabeled Videos.

Ruohan Gao, Dinesh Jayaraman, Kristen Grauman

Proceedings of the Computer Vision - ACCV 2016, 2016

2015

Learning image representations equivariant to ego-motion.

Dinesh Jayaraman, Kristen Grauman

CoRR, 2015

Learning Image Representations Tied to Ego-Motion.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014

Zero-shot recognition with unreliable attributes.

Dinesh Jayaraman, Kristen Grauman

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Decorrelating Semantic Visual Attributes by Resisting the Urge to Share.

Dinesh Jayaraman, Fei Sha, Kristen Grauman

Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2012

Objective quality assessment of multiply distorted images.

Dinesh Jayaraman, Anish Mittal, Anush K. Moorthy, Alan C. Bovik

Proceedings of the Conference Record of the Forty Sixth Asilomar Conference on Signals, 2012