306 citations · 419 across the 12 of their papers we have counts for
5 papers · 1 filter
Visual Prompting via Image Inpainting
Amir Bar, Yossi Gandelsman, Trevor Darrell +2
How does one adapt a pre-trained visual model to novel downstream tasks without task-specific finetuning or any model modification? Inspired by prompting in NLP, this paper investi…
Learning Pixel Trajectories with Multiscale Contrastive Random Walks
Zhangxing Bian, Allan Jabri, Alexei A. Efros +1
A range of video modeling tasks, from optical flow to multiple object tracking, share the same fundamental challenge: establishing space-time correspondence. Yet, approaches that d…
GAN-Supervised Dense Visual Alignment
William Peebles, Jun-Yan Zhu, Richard Zhang +3
We propose GAN-Supervised Learning, a framework for learning discriminative models and their GAN-generated training data jointly end-to-end. We apply our framework to the dense vis…
A 4D Light-Field Dataset and CNN Architectures for Material Recognition
Ting-Chun Wang, Jun-Yan Zhu, Ebi Hiroaki +3
We introduce a new light-field dataset of materials, and take advantage of the recent success of deep learning to perform material recognition on the 4D light-field. Our dataset co…
What makes ImageNet good for transfer learning?
Minyoung Huh, Pulkit Agrawal, Alexei A. Efros
The tremendous success of ImageNet-trained deep features on a wide range of transfer tasks begs the question: what are the properties of the ImageNet dataset that are critical for…