66 citations · 247 across the 40 of their papers we have counts for
3 papers · 1 filter
Unlocking the Full Potential of Small Data with Diverse Supervision
Ziqi Pang, Zhiyuan Hu, Pavel Tokmakov +2
Virtually all of deep learning literature relies on the assumption of large amounts of available training data. Indeed, even the majority of few-shot learning methods rely on a lar…
Growing a Brain: Fine-Tuning by Increasing Model Capacity
Yu-Xiong Wang, Deva Ramanan, Martial Hebert
CNNs have made an undeniable impact on computer vision through the ability to learn high-capacity models with large annotated training sets. One of their remarkable properties is t…
Image Deformation Meta-Networks for One-Shot Learning
Zitian Chen, Yanwei Fu, Yu-Xiong Wang +3
Humans can robustly learn novel visual concepts even when images undergo various deformations and lose certain information. Mimicking the same behavior and synthesizing deformed in…