Malik, Jitendra

PONI: Potential Functions for ObjectGoal Navigation with Interaction-free Learning

Ramakrishnan, S. K., Chaplot, D. S., Al-Halah, Z., Malik, J., & Grauman, K. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 154

Iterative Instance Segmentation

Li, K., Hariharan, B., & Malik, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 152

Distribution-free, Risk-controlling Prediction Sets

Bates, S., Angelopoulos, A., Lei, L., Malik, J., & Jordan, M. (2021) · Journal of the ACM

Adversarial Robustness in Machine LearningMachine Learning and Algorithms

Cited by 144

Habitat 2.0: Training home assistants to rearrange their habitat

Szot, A., Clegg, A., Undersander, E., Wijmans, E., Zhao, Y., Turner, J., Maestre, N., Mukadam, M., Chaplot, D., Maksymets, O., et al. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 143

Navigating to objects in the real world

Gervet, T., Chintala, S., Batra, D., Malik, J., & Chaplot, D. S. (2023) · Science Robotics

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 125

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

Rearrangement: A Challenge for Embodied AI

Batra, D., Chang, A. X., Chernova, S., Davison, A. J., Deng, J., Koltun, V., Levine, S., Malik, J., Mordatch, I., Mottaghi, R., et al. (2020) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 109

Object Instance Segmentation and Fine-Grained Localization Using Hypercolumns

Hariharan, B., Arbelaez, P., Girshick, R., & Malik, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 102

Diverse Image Synthesis From Semantic Layouts via Conditional IMLE

Li, K., Zhang, T., & Malik, J. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image Synthesis3D Shape Modeling and Analysis

Cited by 91

Legged Locomotion in Challenging Terrains using Egocentric Vision

Agarwal, A., Kumar, A., Malik, J., & Pathak, D. (2022) · arXiv

Robotic Locomotion and ControlReinforcement Learning in Robotics

Cited by 82

Uncertainty Sets for Image Classifiers using Conformal Prediction

Angelopoulos, A., Bates, S., Malik, J., & Jordan, M. I. (2020) · arXiv

Adversarial Robustness in Machine LearningAdvanced Neural Network Applications

Cited by 79

GOAT: GO to Any Thing

Chang, M., Gervet, T., Khanna, M., Yenamandra, S., Shah, D., Min, S., Shah, K., Paxton, C., Gupta, S., Batra, D., et al. (2024) · Robotics: Science and Systems XX

Robot Manipulation and LearningRobotics and Sensor-Based Localization

Cited by 53

Interactive Task Planning with Language Models

Li, B., Wu, P., Abbeel, P., & Malik, J. (2023) · arXiv

Robot Manipulation and LearningAI-based Problem Solving and Planning

Cited by 41

Navigating to Objects Specified by Images

Krantz, J., Gervet, T., Yadav, K., Wang, A., Paxton, C., Mottaghi, R., Batra, D., Malik, J., Lee, S., & Singh Chaplot, D. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Reinforcement Learning in RoboticsRobotics and Sensor-Based Localization

Cited by 34

General in-hand object rotation with vision and touch

Qi, H., Yi, B., Suresh, S., Lambeta, M., Ma, Y., Calandra, R., & Malik, J. (2023) · arXiv

Robot Manipulation and LearningInteractive and Immersive Displays

Cited by 33

SEAL: Self-supervised embodied active learning using exploration and 3D consistency

Chaplot, D. S., Dalal, M., Gupta, S., Malik, J., & Salakhutdinov, R. (2021) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 22

Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Lekeufack, J., Angelopoulos, A. N., Bajcsy, A., Jordan, M. I., & Malik, J. (2024) · 2024 IEEE International Conference on Robotics and Automation (ICRA)

Machine Learning and AlgorithmsAdversarial Robustness in Machine Learning

Cited by 18

Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots

Puig, X., Undersander, E., Szot, A., Cote, M. D., Yang, T.-Y., Partsey, R., Desai, R., Clegg, A. W., Hlavac, M., Min, S. Y., et al. (2023) · arXiv

Robot Manipulation and LearningSocial Robot Interaction and HRI

Cited by 15

Volumetric Semantic Segmentation Using Pyramid Context Features

Barron, J. T., Biggin, M. D., Arbelaez, P., Knowles, D. W., Keranen, S. V. E., & Malik, J. (2013) · 2013 IEEE International Conference on Computer Vision

Cell Image Analysis TechniquesAdvanced Neural Network Applications

Cited by 15

Detecting people in Cubist art

Ginosar, S., Haas, D., Brown, T., & Malik, J. (2015) · AI Matters

Advanced Neural Network ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 12

Instance-Specific Image Goal Navigation: Training Embodied Agents to Find Object Instances

Krantz, J., Lee, S., Malik, J., Batra, D., & Chaplot, D. S. (2022) · arXiv

Reinforcement Learning in RoboticsSpatial Cognition and Navigation

Cited by 7

Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives

Grauman, K., Westbury, A., Torresani, L., Kitani, K., Malik, J., Afouras, T., Ashutosh, K., Baiyya, V., Bansal, S., Boote, B., et al. (2025) · International Journal of Computer Vision

Human Pose and Action RecognitionContext-Aware Activity Recognition Systems

Cited by 3

AutoEval Done Right: Using Synthetic Data for Model Evaluation

Boyeau, P., Angelopoulos, A. N., Yosef, N., Malik, J., & Jordan, M. I. (2024) · arXiv

Machine Learning and Data ClassificationMachine Learning and Algorithms

Cited by 1

An Empirical Study of Autoregressive Pre-Training from Videos

Rajasegaran, J., Radosavovic, I., Ravishankar, R., Gandelsman, Y., Feichtenhofer, C., & Malik, J. (2025) · arXiv

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 0