Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata +4

Deep Object-Centric Representations for Generalizable Robot Learning

Coline Devin, Pieter Abbeel, Trevor Darrell +1

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

Ronghang Hu, Jacob Andreas, Marcus Rohrbach +2

Simultaneous Deep Transfer Across Domains and Tasks

Eric Tzeng, Judy Hoffman, Trevor Darrell +1

Multi-View Learning in the Presence of View Disagreement

C. Christoudias, Raquel Urtasun, Trevor Darrell

Multi-Content GAN for Few-Shot Font Style Transfer

Samaneh Azadi, Matthew Fisher, Vladimir Kim +3

DeepSentiBank: Visual Sentiment Concept Classification with Deep Convolutional Neural Networks

Tao Chen, Damian Borth, Trevor Darrell +1

Deep Domain Confusion: Maximizing for Domain Invariance

Eric Tzeng, Judy Hoffman, Ning Zhang +2

Do Convnets Learn Correspondence?

Jonathan Long, Ning Zhang, Trevor Darrell

Fully Convolutional Networks for Semantic Segmentation

Evan Shelhamer, Jonathan Long, Trevor Darrell

Explainable Neural Computation via Stack Neural Module Networks

Ronghang Hu, Jacob Andreas, Trevor Darrell +1

Rethinking the Value of Network Pruning

Zhuang Liu, Mingjie Sun, Tinghui Zhou +2

Object Hallucination in Image Captioning

Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns +2

Attentive Explanations: Justifying Decisions and Pointing to the Evidence

Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata +3

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

Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha +2

Grounding of Textual Phrases in Images by Reconstruction

Anna Rohrbach, Marcus Rohrbach, Ronghang Hu +2

Quantification in-the-wild: data-sets and baselines

Oscar Beijbom, Judy Hoffman, Evan Yao +4

Localizing Moments in Video with Natural Language

Lisa Anne Hendricks, Oliver Wang, Eli Shechtman +3

Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data

Lisa Anne Hendricks, Subhashini Venugopalan, Marcus Rohrbach +3

Mapping Images to Sentiment Adjective Noun Pairs with Factorized Neural Nets

Takuya Narihira, Damian Borth, Stella X. Yu +2

Weakly-supervised Discovery of Visual Pattern Configurations

Hyun Oh Song, Yong Jae Lee, Stefanie Jegelka +1

Learning to Compose Neural Networks for Question Answering

Jacob Andreas, Marcus Rohrbach, Trevor Darrell +1

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

Lisa Anne Hendricks, Kaylee Burns, Kate Saenko +2

Dynamic Scale Inference by Entropy Minimization

Dequan Wang, Evan Shelhamer, Bruno Olshausen +1

The paper introduces an iterative inference method that predicts and adapts the scale of visual features using an entropy minimization objective, improving semantic segmentation un…

Fully Convolutional Networks for Semantic Segmentation

Jonathan Long, Evan Shelhamer, Trevor Darrell

Gradient-free Policy Architecture Search and Adaptation

Sayna Ebrahimi, Anna Rohrbach, Trevor Darrell

Constrained Structured Regression with Convolutional Neural Networks

Deepak Pathak, Philipp Krähenbühl, Stella X. Yu +1

Discriminator Rejection Sampling

Samaneh Azadi, Catherine Olsson, Trevor Darrell +2

Monocular Plan View Networks for Autonomous Driving

Dequan Wang, Coline Devin, Qi-Zhi Cai +2

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

Huazhe Xu, Yang Gao, Fisher Yu +1

Why Size Matters: Feature Coding as Nystrom Sampling

Oriol Vinyals, Yangqing Jia, Trevor Darrell

Data-dependent Initializations of Convolutional Neural Networks

Philipp Krähenbühl, Carl Doersch, Jeff Donahue +1

Deep Layer Aggregation

Fisher Yu, Dequan Wang, Evan Shelhamer +1

Constrained Convolutional Neural Networks for Weakly Supervised Segmentation

Deepak Pathak, Philipp Krähenbühl, Trevor Darrell

Learning Instance Segmentation by Interaction

Deepak Pathak, Yide Shentu, Dian Chen +4

Rich feature hierarchies for accurate object detection and semantic segmentation

Ross Girshick, Jeff Donahue, Trevor Darrell +1

Captioning Images with Diverse Objects

Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach +3

Auxiliary Image Regularization for Deep CNNs with Noisy Labels

Samaneh Azadi, Jiashi Feng, Stefanie Jegelka +1

Zero-Shot Visual Imitation

Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo +7

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

Jeff Donahue, Yangqing Jia, Oriol Vinyals +4

Neural Module Networks

Jacob Andreas, Marcus Rohrbach, Trevor Darrell +1

Deep Spatial Autoencoders for Visuomotor Learning

Chelsea Finn, Xin Yu Tan, Yan Duan +3

Disentangling Propagation and Generation for Video Prediction

Hang Gao, Huazhe Xu, Qi-Zhi Cai +3

The paper proposes a video prediction model that separates motion-based warping from generative inpainting, using a confidence-aware warping operator to handle non‑occluded and occ…

Part-based R-CNNs for Fine-grained Category Detection

Ning Zhang, Jeff Donahue, Ross Girshick +1

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints

Eric Tzeng, Coline Devin, Judy Hoffman +5

Robust Change Captioning

Dong Huk Park, Trevor Darrell, Anna Rohrbach

Long-term Recurrent Convolutional Networks for Visual Recognition and Description

Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach +4

SkipNet: Learning Dynamic Routing in Convolutional Networks

Xin Wang, Fisher Yu, Zi-Yi Dou +2

Speaker-Follower Models for Vision-and-Language Navigation

Daniel Fried, Ronghang Hu, Volkan Cirik +7

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

Judy Hoffman, Deepak Pathak, Trevor Darrell +1

Deep Learning for Tactile Understanding From Visual and Haptic Data

Yang Gao, Lisa Anne Hendricks, Katherine J. Kuchenbecker +1

Factorized Multi-Modal Topic Model

Seppo Virtanen, Yangqing Jia, Arto Klami +1

Clockwork Convnets for Video Semantic Segmentation

Evan Shelhamer, Kate Rakelly, Judy Hoffman +1

Deep Mixture of Experts via Shallow Embedding

Xin Wang, Fisher Yu, Lisa Dunlap +5

Textual Explanations for Self-Driving Vehicles

Jinkyu Kim, Anna Rohrbach, Trevor Darrell +2

Curiosity-driven Exploration by Self-supervised Prediction

Deepak Pathak, Pulkit Agrawal, Alexei A. Efros +1

Learning Detection with Diverse Proposals

Samaneh Azadi, Jiashi Feng, Trevor Darrell

Women also Snowboard: Overcoming Bias in Captioning Models

Kaylee Burns, Lisa Anne Hendricks, Kate Saenko +2

Compact Bilinear Pooling

Yang Gao, Oscar Beijbom, Ning Zhang +1

Modular Architecture for StarCraft II with Deep Reinforcement Learning

Dennis Lee, Haoran Tang, Jeffrey O Zhang +3

SPLAT: Semantic Pixel-Level Adaptation Transforms for Detection

Eric Tzeng, Kaylee Burns, Kate Saenko +1

Fine-grained pose prediction, normalization, and recognition

Ning Zhang, Evan Shelhamer, Yang Gao +1

Pooling-Invariant Image Feature Learning

Yangqing Jia, Oriol Vinyals, Trevor Darrell

One-Shot Adaptation of Supervised Deep Convolutional Models

Judy Hoffman, Eric Tzeng, Jeff Donahue +3

Spatial Semantic Regularisation for Large Scale Object Detection

Damian Mrowca, Marcus Rohrbach, Judy Hoffman +3

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

Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata +4

Hierarchical Discrete Distribution Decomposition for Match Density Estimation

Zhichao Yin, Trevor Darrell, Fisher Yu

Grounding Visual Explanations (Extended Abstract)

Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell +1

Compositional GAN: Learning Image-Conditional Binary Composition

Samaneh Azadi, Deepak Pathak, Sayna Ebrahimi +1

Toward Multimodal Image-to-Image Translation

Jun-Yan Zhu, Richard Zhang, Deepak Pathak +4

Grounding Visual Explanations

Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell +1

Context Encoders: Feature Learning by Inpainting

Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue +2

Sequence to Sequence -- Video to Text

Subhashini Venugopalan, Marcus Rohrbach, Jeff Donahue +3

Adversarial Inference for Multi-Sentence Video Description

Jae Sung Park, Marcus Rohrbach, Trevor Darrell +1

Generating Counterfactual Explanations with Natural Language

Lisa Anne Hendricks, Ronghang Hu, Trevor Darrell +1

Fully Convolutional Multi-Class Multiple Instance Learning

Deepak Pathak, Evan Shelhamer, Jonathan Long +1

Loss is its own Reward: Self-Supervision for Reinforcement Learning

Evan Shelhamer, Parsa Mahmoudieh, Max Argus +1

On learning to localize objects with minimal supervision

Hyun Oh Song, Ross Girshick, Stefanie Jegelka +3

Learning to Segment Every Thing

Ronghang Hu, Piotr Dollár, Kaiming He +2

Fooling Vision and Language Models Despite Localization and Attention Mechanism

Xiaojun Xu, Xinyun Chen, Chang Liu +3

Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer

Coline Devin, Abhishek Gupta, Trevor Darrell +2

Learning Compact Convolutional Neural Networks with Nested Dropout

Chelsea Finn, Lisa Anne Hendricks, Trevor Darrell

Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations

Erik Rodner, Judy Hoffman, Jeff Donahue +2

Similarity R-C3D for Few-shot Temporal Activity Detection

Huijuan Xu, Bingyi Kang, Ximeng Sun +3

Natural Language Object Retrieval

Ronghang Hu, Huazhe Xu, Marcus Rohrbach +3

Generalized orderless pooling performs implicit salient matching

Marcel Simon, Yang Gao, Trevor Darrell +2

Visual Discovery at Pinterest

Andrew Zhai, Dmitry Kislyuk, Yushi Jing +5

DenseNet: Implementing Efficient ConvNet Descriptor Pyramids

Forrest Iandola, Matt Moskewicz, Sergey Karayev +3

Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions

Ronghang Hu, Marcus Rohrbach, Subhashini Venugopalan +1

Few-Shot Segmentation Propagation with Guided Networks

Kate Rakelly, Evan Shelhamer, Trevor Darrell +2

TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning

Xin Wang, Fisher Yu, Ruth Wang +2

Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition

Tim Althoff, Hyun Oh Song, Trevor Darrell

Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation

Ronghang Hu, Daniel Fried, Anna Rohrbach +3

Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding

Akira Fukui, Dong Huk Park, Daylen Yang +3

Modeling Radiometric Uncertainty for Vision with Tone-mapped Color Images

Ayan Chakrabarti, Ying Xiong, Baochen Sun +4

Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields

Evan Shelhamer, Dequan Wang, Trevor Darrell

PANDA: Pose Aligned Networks for Deep Attribute Modeling

Ning Zhang, Manohar Paluri, Marc'Aurelio Ranzato +2

Generating Visual Explanations

Lisa Anne Hendricks, Zeynep Akata, Marcus Rohrbach +3

Localizing Moments in Video with Temporal Language

Lisa Anne Hendricks, Oliver Wang, Eli Shechtman +3

Reinforcement Learning from Imperfect Demonstrations

Yang Gao, Huazhe Xu, Ji Lin +3