Trevor Darrell

Textual Explanations for Self-Driving Vehicles

Jinkyu Kim, Anna Rohrbach, Trevor Darrell, John Canny, Zeynep Akata

Comments Accepted to ECCV 2018

Journal ref European Conference on Computer Vision (ECCV), 2018

SkipNet: Learning Dynamic Routing in Convolutional Networks

Xin Wang, Fisher Yu, Zi-Yi Dou, Trevor Darrell, Joseph E. Gonzalez

Comments ECCV 2018 Camera ready version. Code is available at https://github.com/ucbdrive/skipnet

Women also Snowboard: Overcoming Bias in Captioning Models (Extended Abstract)

Lisa Anne Hendricks, Kaylee Burns, Kate Saenko, Trevor Darrell, Anna Rohrbach

Comments Burns and Hendricks contributed equally. 2018 ICML Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2018)

Generating Counterfactual Explanations with Natural Language

Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell, Zeynep Akata

Comments presented at 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018), Stockholm, Sweden

Learning Instance Segmentation by Interaction

Deepak Pathak, Yide Shentu, Dian Chen, Pulkit Agrawal, Trevor Darrell, Sergey Levine, Jitendra Malik

Comments Website at https://pathak22.github.io/seg-by-interaction/

Few-Shot Segmentation Propagation with Guided Networks

Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alexei A. Efros, Sergey Levine

Zero-Shot Visual Imitation

Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell

Comments Oral presentation at ICLR 2018. Website at https://pathak22.github.io/zeroshot-imitation/

Fooling Vision and Language Models Despite Localization and Attention Mechanism

Xiaojun Xu, Xinyun Chen, Chang Liu, Anna Rohrbach, Trevor Darrell, Dawn Song

Comments CVPR 2018

Learning to Segment Every Thing

Ronghang Hu, Piotr Dollár, Kaiming He, Trevor Darrell, Ross Girshick

Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata, Anna Rohrbach, Bernt Schiele, Trevor Darrell, Marcus Rohrbach

Comments arXiv admin note: text overlap with arXiv:1612.04757

Recasting Gradient-Based Meta-Learning as Hierarchical Bayes

Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas Griffiths

CyCADA: Cycle-Consistent Adversarial Domain Adaptation

Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei A. Efros, Trevor Darrell

Multi-Content GAN for Few-Shot Font Style Transfer

Samaneh Azadi, Matthew Fisher, Vladimir Kim, Zhaowen Wang, Eli Shechtman, Trevor Darrell

Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)

Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata, Anna Rohrbach, Bernt Schiele, Trevor Darrell, Marcus Rohrbach

Comments arXiv admin note: text overlap with arXiv:1612.04757

Grounding Visual Explanations (Extended Abstract)

Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell, Zeynep Akata

Comments Presented at NIPS 2017 Symposium on Interpretable Machine Learning

Detector Discovery in the Wild: Joint Multiple Instance and Representation Learning

Judy Hoffman, Deepak Pathak, Trevor Darrell, Kate Saenko

Journal ref Computer Vision and Pattern Recognition (CVPR) 2015

LSDA: Large Scale Detection Through Adaptation

Judy Hoffman, Sergio Guadarrama, Eric Tzeng, Ronghang Hu, Jeff Donahue, Ross Girshick, Trevor Darrell, Kate Saenko

Journal ref Neural Information Processing Systems (NIPS) 2014

One-Shot Adaptation of Supervised Deep Convolutional Models

Judy Hoffman, Eric Tzeng, Jeff Donahue, Yangqing Jia, Kate Saenko, Trevor Darrell

Journal ref ICLR Workshop 2014

Efficient Learning of Domain-invariant Image Representations

Judy Hoffman, Erik Rodner, Jeff Donahue, Trevor Darrell, Kate Saenko

Journal ref ICLR 2013

Gradient-free Policy Architecture Search and Adaptation

Sayna Ebrahimi, Anna Rohrbach, Trevor Darrell

Comments Accepted in Conference on Robot Learning, 2017

Deep Object-Centric Representations for Generalizable Robot Learning

Coline Devin, Pieter Abbeel, Trevor Darrell, Sergey Levine

Learning to Reason: End-to-End Module Networks for Visual Question Answering

Ronghang Hu, Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Kate Saenko

Localizing Moments in Video with Natural Language

Lisa Anne Hendricks, Oliver Wang, Eli Shechtman, Josef Sivic, Trevor Darrell, Bryan Russell

Comments ICCV 2017

Attentive Explanations: Justifying Decisions and Pointing to the Evidence

Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata, Bernt Schiele, Trevor Darrell, Marcus Rohrbach

Neural Module Networks

Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein

Comments Corrects an error in the evaluation of the NMN-only ablation experiment

End-to-end Learning of Driving Models from Large-scale Video Datasets

Huazhe Xu, Yang Gao, Fisher Yu, Trevor Darrell

Comments camera ready for CVPR2017

Captioning Images with Diverse Objects

Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Raymond Mooney, Trevor Darrell, Kate Saenko

Comments CVPR 2017 Camera ready version. 17 pages (8 + 9 supplement), 12 figures, 8 tables. Includes project page http://vsubhashini.github.io/noc.html

Generalized orderless pooling performs implicit salient matching

Marcel Simon, Yang Gao, Trevor Darrell, Joachim Denzler, Erik Rodner

Comments Published at International Conference on Computer Vision (ICCV) 2017

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints

Eric Tzeng, Coline Devin, Judy Hoffman, Chelsea Finn, Pieter Abbeel, Sergey Levine, Kate Saenko, Trevor Darrell

Curiosity-driven Exploration by Self-supervised Prediction

Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell

Comments In ICML 2017. Website at https://pathak22.github.io/noreward-rl/