2.3k citations · 7.8k across the 98 of their papers we have counts for
14 papers · 1 filter
Dataset Distillation
Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba +1
Model distillation aims to distill the knowledge of a complex model into a simpler one. In this paper, we consider an alternative formulation called dataset distillation: we keep t…
Improving Generalization via Scalable Neighborhood Component Analysis
Zhirong Wu, Alexei A. Efros, Stella X. Yu
Current major approaches to visual recognition follow an end-to-end formulation that classifies an input image into one of the pre-determined set of semantic categories. Parametric…
Large-Scale Study of Curiosity-Driven Learning
Yuri Burda, Harri Edwards, Deepak Pathak +3
Reinforcement learning algorithms rely on carefully engineering environment rewards that are extrinsic to the agent. However, annotating each environment with hand-designed, dense…
Time-Agnostic Prediction: Predicting Predictable Video Frames
Dinesh Jayaraman, Frederik Ebert, Alexei A. Efros +1
Prediction is arguably one of the most basic functions of an intelligent system. In general, the problem of predicting events in the future or between two waypoints is exceedingly…
Everybody Dance Now
Caroline Chan, Shiry Ginosar, Tinghui Zhou +1
This paper presents a simple method for "do as I do" motion transfer: given a source video of a person dancing, we can transfer that performance to a novel (amateur) target after o…
Few-Shot Segmentation Propagation with Guided Networks
Kate Rakelly, Evan Shelhamer, Trevor Darrell +2
Learning-based methods for visual segmentation have made progress on particular types of segmentation tasks, but are limited by the necessary supervision, the narrow definitions of…
Fighting Fake News: Image Splice Detection via Learned Self-Consistency
Minyoung Huh, Andrew Liu, Andrew Owens +1
Advances in photo editing and manipulation tools have made it significantly easier to create fake imagery. Learning to detect such manipulations, however, remains a challenging pro…
Zero-Shot Visual Imitation
Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo +7
The current dominant paradigm for imitation learning relies on strong supervision of expert actions to learn both 'what' and 'how' to imitate. We pursue an alternative paradigm whe…
Audio-Visual Scene Analysis with Self-Supervised Multisensory Features
Andrew Owens, Alexei A. Efros
The thud of a bouncing ball, the onset of speech as lips open -- when visual and audio events occur together, it suggests that there might be a common, underlying event that produc…
Learning Beyond Human Expertise with Generative Models for Dental Restorations
Jyh-Jing Hwang, Sergei Azernikov, Alexei A. Efros +1
Computer vision has advanced significantly that many discriminative approaches such as object recognition are now widely used in real applications. We present another exciting deve…
Learning Category-Specific Mesh Reconstruction from Image Collections
Angjoo Kanazawa, Shubham Tulsiani, Alexei A. Efros +1
We present a learning framework for recovering the 3D shape, camera, and texture of an object from a single image. The shape is represented as a deformable 3D mesh model of an obje…
Investigating Human Priors for Playing Video Games
Rachit Dubey, Pulkit Agrawal, Deepak Pathak +2
What makes humans so good at solving seemingly complex video games? Unlike computers, humans bring in a great deal of prior knowledge about the world, enabling efficient decision m…
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
Richard Zhang, Phillip Isola, Alexei A. Efros +2
While it is nearly effortless for humans to quickly assess the perceptual similarity between two images, the underlying processes are thought to be quite complex. Despite this, the…
Multi-view Consistency as Supervisory Signal for Learning Shape and Pose Prediction
Shubham Tulsiani, Alexei A. Efros, Jitendra Malik
We present a framework for learning single-view shape and pose prediction without using direct supervision for either. Our approach allows leveraging multi-view observations from u…