56 citations · 257 across the 54 of their papers we have counts for
6 papers · 1 filter
Detecting Cross-Modal Inconsistency to Defend Against Neural Fake News
Reuben Tan, Bryan A. Plummer, Kate Saenko
Large-scale dissemination of disinformation online intended to mislead or deceive the general population is a major societal problem. Rapid progression in image, video, and natural…
Self-supervised Visual Attribute Learning for Fashion Compatibility
Donghyun Kim, Kuniaki Saito, Samarth Mishra +3
Many self-supervised learning (SSL) methods have been successful in learning semantically meaningful visual representations by solving pretext tasks. However, prior work in SSL foc…
Neural Parameter Allocation Search
Bryan A. Plummer, Nikoli Dryden, Julius Frost +2
Training neural networks requires increasing amounts of memory. Parameter sharing can reduce memory and communication costs, but existing methods assume networks have many identica…
Learning to Scale Multilingual Representations for Vision-Language Tasks
Andrea Burns, Donghyun Kim, Derry Wijaya +2
Current multilingual vision-language models either require a large number of additional parameters for each supported language, or suffer performance degradation as languages are a…
Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels
Donghyun Kim, Kuniaki Saito, Tae-Hyun Oh +3
Existing unsupervised domain adaptation methods aim to transfer knowledge from a label-rich source domain to an unlabeled target domain. However, obtaining labels for some source d…
MILA: Multi-Task Learning from Videos via Efficient Inter-Frame Attention
Donghyun Kim, Tian Lan, Chuhang Zou +5
Prior work in multi-task learning has mainly focused on predictions on a single image. In this work, we present a new approach for multi-task learning from videos via efficient int…