2.4k citations · 7.8k across the 82 of their papers we have counts for
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SkipNet: Learning Dynamic Routing in Convolutional Networks
Xin Wang, Fisher Yu, Zi-Yi Dou +2
While deeper convolutional networks are needed to achieve maximum accuracy in visual perception tasks, for many inputs shallower networks are sufficient. We exploit this observatio…
Deep Layer Aggregation
Fisher Yu, Dequan Wang, Evan Shelhamer +1
Visual recognition requires rich representations that span levels from low to high, scales from small to large, and resolutions from fine to coarse. Even with the depth of features…
Interactive 3D Modeling with a Generative Adversarial Network
Jerry Liu, Fisher Yu, Thomas Funkhouser
This paper proposes the idea of using a generative adversarial network (GAN) to assist a novice user in designing real-world shapes with a simple interface. The user edits a voxel…
TextureGAN: Controlling Deep Image Synthesis with Texture Patches
Wenqi Xian, Patsorn Sangkloy, Varun Agrawal +5
In this paper, we investigate deep image synthesis guided by sketch, color, and texture. Previous image synthesis methods can be controlled by sketch and color strokes but we are t…
IDK Cascades: Fast Deep Learning by Learning not to Overthink
Xin Wang, Yujia Luo, Daniel Crankshaw +3
Advances in deep learning have led to substantial increases in prediction accuracy but have been accompanied by increases in the cost of rendering predictions. We conjecture that f…
Dilated Residual Networks
Fisher Yu, Vladlen Koltun, Thomas Funkhouser
Convolutional networks for image classification progressively reduce resolution until the image is represented by tiny feature maps in which the spatial structure of the scene is n…