25 citations · 42 across the 4 of their papers we have counts for
5 papers · 1 filter
Multimodal Contrastive Training for Visual Representation Learning
Xin Yuan, Zhe Lin, Jason Kuen +5
We develop an approach to learning visual representations that embraces multimodal data, driven by a combination of intra- and inter-modal similarity preservation objectives. Unlik…
Self-Supervised Visual Representation Learning from Hierarchical Grouping
Xiao Zhang, Michael Maire
We create a framework for bootstrapping visual representation learning from a primitive visual grouping capability. We operationalize grouping via a contour detector that partition…
Information-Theoretic Segmentation by Inpainting Error Maximization
Pedro Savarese, Sunnie S. Y. Kim, Michael Maire +2
We study image segmentation from an information-theoretic perspective, proposing a novel adversarial method that performs unsupervised segmentation by partitioning images into maxi…
Pixel Consensus Voting for Panoptic Segmentation
Haochen Wang, Ruotian Luo, Michael Maire +1
The core of our approach, Pixel Consensus Voting, is a framework for instance segmentation based on the Generalized Hough transform. Pixels cast discretized, probabilistic votes fo…
Regularizing Deep Networks by Modeling and Predicting Label Structure
Mohammadreza Mostajabi, Michael Maire, Gregory Shakhnarovich
We construct custom regularization functions for use in supervised training of deep neural networks. Our technique is applicable when the ground-truth labels themselves exhibit int…