Darrell, Trevor

Fully convolutional networks for semantic segmentation

Long, J., Shelhamer, E., & Darrell, T. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 38,834

Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 32,684

Fully convolutional networks for semantic segmentation

Shelhamer, E., Long, J., & Darrell, T. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 11,898

Caffe: Convolutional Architecture for Fast Feature Embedding

Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., & Darrell, T. (2014) · Proceedings of the 22nd ACM international conference on Multimedia

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 11,077

A ConvNet for the 2020s

Liu, Z., Mao, H., Wu, C.-Y., Feichtenhofer, C., Darrell, T., & Xie, S. (2022) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 8,924

A ConvNet for the 2020s

Liu, Z., Mao, H., Wu, C.-Y., Feichtenhofer, C., Darrell, T., & Xie, S. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 8,494

Context Encoders: Feature Learning by Inpainting

Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., & Efros, A. A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 5,691

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

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

Donahue, J., Jia, Y., Vinyals, O., Hoffman, J., Zhang, N., Tzeng, E., & Darrell, T. (2013) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 4,019

Region-based convolutional networks for accurate object detection and segmentation

Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 2,912

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

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning

Yu, F., Chen, H., Wang, X., Xian, W., Chen, Y., Liu, F., Madhavan, V., & Darrell, T. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 2,641

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

Curiosity-Driven Exploration by Self-Supervised Prediction

Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 1,815

Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding

Fukui, A., Park, D. H., Yang, D., Rohrbach, A., Darrell, T., & Rohrbach, M. (2016) · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing

Multimodal Machine Learning ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 1,582

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

End-to-End Learning of Driving Models from Large-Scale Video Datasets

Xu, H., Gao, Y., Yu, F., & Darrell, T. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Autonomous Vehicle Technology and SafetyReinforcement Learning in Robotics

Cited by 884

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

Schönfeld, E., Ebrahimi, S., Sinha, S., Darrell, T., & Akata, Z. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 747

Generating Visual Explanations

Hendricks, L. A., Akata, Z., Rohrbach, M., Donahue, J., Schiele, B., & Darrell, T. (2016) · Lecture Notes in Computer Science

Multimodal Machine Learning ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 534

Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning

Chen, Y., Liu, Z., Xu, H., Darrell, T., & Wang, X. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 503

PANDA: Pose Aligned Networks for Deep Attribute Modeling

Zhang, N., Paluri, M., Ranzato, M., Darrell, T., & Bourdev, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsFace recognition and analysis

Cited by 495

Quasi-Dense Similarity Learning for Multiple Object Tracking

Pang, J., Qiu, L., Li, X., Chen, H., Li, Q., Darrell, T., & Yu, F. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 480