Kira, Zsolt

Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data

Hsu, Y.-C., Shen, Y., Jin, H., & Kira, Z. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Adversarial Robustness in Machine LearningDigital Media Forensic Detection

Cited by 499

Biological underpinnings for lifelong learning machines

Kudithipudi, D., Aguilar-Simon, M., Babb, J., Bazhenov, M., Blackiston, D., Bongard, J., Brna, A. P., Chakravarthi Raja, S., Cheney, N., Clune, J., et al. (2022) · Nature Machine Intelligence

Domain Adaptation and Few-Shot LearningNeural Networks and Applications

Cited by 236

Self-Monitoring Navigation Agent via Auxiliary Progress Estimation

Ma, C.-Y., Lu, J., Wu, Z., AlRegib, G., Kira, Z., Socher, R., & Xiong, C. (2019) · arXiv

Multimodal Machine Learning ApplicationsReinforcement Learning in Robotics

Cited by 200

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

Diffuse, Attend, and Segment: Unsupervised Zero-Shot Segmentation using Stable Diffusion

Tian, J., Aggarwal, L., Colaco, A., Kira, Z., & Gonzalez-Franco, M. (2023) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 96

Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation

Maheshwari, H., Liu, Y.-C., & Kira, Z. (2024) · 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 37

Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA

Smith, J. S., Hsu, Y.-C., Zhang, L., Hua, T., Kira, Z., Shen, Y., & Jin, H. (2023) · arXiv

Generative Adversarial Networks and Image SynthesisDomain Adaptation and Few-Shot Learning

Cited by 25

GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation

Khanna, M., Ramrakhya, R., Chhablani, G., Yenamandra, S., Gervet, T., Chang, M., Kira, Z., Chaplot, D. S., Batra, D., & Mottaghi, R. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 23

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

Adaptive Coordination in Social Embodied Rearrangement

Szot, A., Jain, U., Batra, D., Kira, Z., Desai, R., & Rai, A. (2023) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 8

Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control

Gupta, G., Yadav, K., Gal, Y., Kira, Z., Batra, D., Lu, C., & Rudner, T. (2024) · Advances in Neural Information Processing Systems 37

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 5

FindingDory: A Benchmark to Evaluate Memory in Embodied Agents

Yadav, K., Ali, Y., Gupta, G., Gal, Y., & Kira, Z. (2025) · arXiv

Multimodal Machine Learning ApplicationsRobot Manipulation and Learning

Cited by 1