2.3k citations · 7.8k across the 98 of their papers we have counts for
10 papers · 1 filter
Morphology-Agnostic Visual Robotic Control
Brian Yang, Dinesh Jayaraman, Glen Berseth +2
Existing approaches for visuomotor robotic control typically require characterizing the robot in advance by calibrating the camera or performing system identification. We propose M…
Unsupervised Curricula for Visual Meta-Reinforcement Learning
Allan Jabri, Kyle Hsu, Ben Eysenbach +3
In principle, meta-reinforcement learning algorithms leverage experience across many tasks to learn fast reinforcement learning (RL) strategies that transfer to similar tasks. Howe…
CNN-generated images are surprisingly easy to spot... for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang +2
In this work we ask whether it is possible to create a "universal" detector for telling apart real images from these generated by a CNN, regardless of architecture or dataset used.…
Unsupervised Domain Adaptation through Self-Supervision
Yu Sun, Eric Tzeng, Trevor Darrell +1
This paper addresses unsupervised domain adaptation, the setting where labeled training data is available on a source domain, but the goal is to have good performance on a target d…
Interactive Sketch & Fill: Multiclass Sketch-to-Image Translation
Arnab Ghosh, Richard Zhang, Puneet K. Dokania +4
We propose an interactive GAN-based sketch-to-image translation method that helps novice users create images of simple objects. As the user starts to draw a sketch of a desired obj…
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts
Yu Sun, Xiaolong Wang, Zhuang Liu +3
In this paper, we propose Test-Time Training, a general approach for improving the performance of predictive models when training and test data come from different distributions. W…
Detecting Photoshopped Faces by Scripting Photoshop
Sheng-Yu Wang, Oliver Wang, Andrew Owens +2
Most malicious photo manipulations are created using standard image editing tools, such as Adobe Photoshop. We present a method for detecting one very popular Photoshop manipulatio…
Learning Correspondence from the Cycle-Consistency of Time
Xiaolong Wang, Allan Jabri, Alexei A. Efros
We introduce a self-supervised method for learning visual correspondence from unlabeled video. The main idea is to use cycle-consistency in time as free supervisory signal for lear…
Discovering Visual Patterns in Art Collections with Spatially-consistent Feature Learning
Xi Shen, Alexei A. Efros, Mathieu Aubry
Our goal in this paper is to discover near duplicate patterns in large collections of artworks. This is harder than standard instance mining due to differences in the artistic medi…
Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity
Deepak Pathak, Chris Lu, Trevor Darrell +2
Contemporary sensorimotor learning approaches typically start with an existing complex agent (e.g., a robotic arm), which they learn to control. In contrast, this paper investigate…