2.4k citations · 7.6k across the 125 of their papers we have counts for
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Exploring Consistency in Cross-Domain Transformer for Domain Adaptive Semantic Segmentation
Kaihong Wang, Donghyun Kim, Rogerio Feris +2
While transformers have greatly boosted performance in semantic segmentation, domain adaptive transformers are not yet well explored. We identify that the domain gap can cause disc…
Bias Mimicking: A Simple Sampling Approach for Bias Mitigation
Maan Qraitem, Kate Saenko, Bryan A. Plummer
Prior work has shown that Visual Recognition datasets frequently underrepresent bias groups (\eg Female) within class labels (\eg Programmers). This dataset bias can lead t…
FETA: Towards Specializing Foundation Models for Expert Task Applications
Amit Alfassy, Assaf Arbelle, Oshri Halimi +10
Foundation Models (FMs) have demonstrated unprecedented capabilities including zero-shot learning, high fidelity data synthesis, and out of domain generalization. However, as we sh…
NewsStories: Illustrating articles with visual summaries
Reuben Tan, Bryan A. Plummer, Kate Saenko +3
Recent self-supervised approaches have used large-scale image-text datasets to learn powerful representations that transfer to many tasks without finetuning. These methods often as…
DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations
Ximeng Sun, Ping Hu, Kate Saenko
Solving multi-label recognition (MLR) for images in the low-label regime is a challenging task with many real-world applications. Recent work learns an alignment between textual an…
Prefix Conditioning Unifies Language and Label Supervision
Kuniaki Saito, Kihyuk Sohn, Xiang Zhang +4
Image-classification datasets have been used to pretrain image recognition models. Recently, web-scale image-caption datasets have emerged as a source of powerful pretraining alter…