Saenko, Kate

Long-term recurrent convolutional networks for visual recognition and description

Donahue, J., Hendricks, L. A., Guadarrama, S., Rohrbach, M., Venugopalan, S., Darrell, T., & Saenko, K. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMultimodal Machine Learning Applications

Cited by 5,228

Adversarial Discriminative Domain Adaptation

Tzeng, E., Hoffman, J., Saenko, K., & Darrell, T. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis

Cited by 5,154

Deep CORAL: Correlation Alignment for Deep Domain Adaptation

Sun, B., & Saenko, K. (2016) · Lecture Notes in Computer Science

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 3,757

Adapting visual category models to new domains

Saenko, K., Kulis, B., Fritz, M., & Darrell, T. (2010) · Lecture Notes in Computer Science

Domain Adaptation and Few-Shot LearningAdvanced Image and Video Retrieval Techniques

Cited by 2,847

CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Hoffman, J., Tzeng, E., Park, T., Zhu, J.-Y., Isola, P., Saenko, K., Efros, A. A., & Darrell, T. (2017) · arXiv

Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis

Cited by 2,656

Deep domain confusion Maximizing for domain invariance

Tzeng, E., Hoffman, J., Zhang, N., Saenko, K., & Darrell, T. (2014) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 2,285

Return of Frustratingly Easy Domain Adaptation

Sun, B., Feng, J., & Saenko, K. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence

Domain Adaptation and Few-Shot LearningReinforcement Learning in Robotics

Cited by 2,004

Return of Frustratingly Easy Domain Adaptation

Sun, B., Feng, J., & Saenko, K. (2015) · arXiv

Domain Adaptation and Few-Shot LearningReinforcement Learning in Robotics

Cited by 2,004

Long-Term Recurrent Convolutional Networks for Visual Recognition and Description

Donahue, J., Hendricks, L. A., Rohrbach, M., Venugopalan, S., Guadarrama, S., Saenko, K., & Darrell, T. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 1,547

Strong-Weak Distribution Alignment for Adaptive Object Detection

Saito, K., Ushiku, Y., Harada, T., & Saenko, K. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 819

Object Hallucination in Image Captioning

Rohrbach, A., Hendricks, L. A., Burns, K., Darrell, T., & Saenko, K. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 420

Women Also Snowboard: Overcoming Bias in Captioning Models

Hendricks, L. A., Burns, K., Saenko, K., Darrell, T., & Rohrbach, A. (2018) · Lecture Notes in Computer Science

Ethics and Social Impacts of AIMultimodal Machine Learning Applications

Cited by 404

Speaker-Follower Models for Vision-and-Language Navigation

Fried, D., Hu, R., Cirik, V., Rohrbach, A., Andreas, J., Morency, L.-P., Berg-Kirkpatrick, T., Saenko, K., Klein, D., & Darrell, T. (2018) · arXiv

Multimodal Machine Learning ApplicationsReinforcement Learning in Robotics

Cited by 291

LSDA: Large Scale Detection Through Adaptation

Hoffman, J., Guadarrama, S., Tzeng, E., Hu, R., Donahue, J., Girshick, R., Darrell, T., & Saenko, K. (2014) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 284

VisDA: A Synthetic-to-Real Benchmark for Visual Domain Adaptation

Peng, X., Usman, B., Kaushik, N., Wang, D., Hoffman, J., & Saenko, K. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 196

AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning

Sun, X., Panda, R., Feris, R., & Saenko, K. (2019) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 169

Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval

Saito, K., Sohn, K., Zhang, X., Li, C.-L., Lee, C.-Y., Saenko, K., & Pfister, T. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Image Retrieval and Classification TechniquesMultimodal Machine Learning Applications

Cited by 145

Fine-grained Angular Contrastive Learning with Coarse Labels

Bukchin, G., Schwartz, E., Saenko, K., Shahar, O., Feris, R., Giryes, R., & Karlinsky, L. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 55

An Introduction to Vision-Language Modeling

Bordes, F., Pang, R. Y., Ajay, A., Li, A. C., Bardes, A., Petryk, S., Mañas, O., Lin, Z., Mahmoud, A., Jayaraman, B., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 47

Spatial Semantic Regularisation for Large Scale Object Detection

Mrowca, D., Rohrbach, M., Hoffman, J., Hu, R., Saenko, K., & Darrell, T. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 20

Prefix Conditioning Unifies Language and Label Supervision

Saito, K., Sohn, K., Zhang, X., Li, C.-L., Lee, C.-Y., Saenko, K., & Pfister, T. (2022) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 17

Is generative AI bad for the environment? A computer scientist explains the carbon footprint of ChatGPT and its cousins

Saenko, K. (2023)

Green IT and SustainabilityEnergy Efficiency in Computing

Cited by 6