4.3k citations · 12.1k across the 37 of their papers we have counts for
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FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation
Judy Hoffman, Dequan Wang, Fisher Yu +1
Fully convolutional models for dense prediction have proven successful for a wide range of visual tasks. Such models perform well in a supervised setting, but performance can be su…
Loss is its own Reward: Self-Supervision for Reinforcement Learning
Evan Shelhamer, Parsa Mahmoudieh, Max Argus +1
Reinforcement learning optimizes policies for expected cumulative reward. Need the supervision be so narrow? Reward is delayed and sparse for many tasks, making it a difficult and…
Modeling Relationships in Referential Expressions with Compositional Modular Networks
Ronghang Hu, Marcus Rohrbach, Jacob Andreas +2
People often refer to entities in an image in terms of their relationships with other entities. For example, "the black cat sitting under the table" refers to both a "black cat" en…
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer
Coline Devin, Abhishek Gupta, Trevor Darrell +2
Reinforcement learning (RL) can automate a wide variety of robotic skills, but learning each new skill requires considerable real-world data collection and manual representation en…
Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions
Ronghang Hu, Marcus Rohrbach, Subhashini Venugopalan +1
Image segmentation from referring expressions is a joint vision and language modeling task, where the input is an image and a textual expression describing a particular region in t…