4 citations · 7 across the 5 of their papers we have counts for
6 papers
MRVQ: One Resident Index for Dimension- and Rate-Elastic Vector Search
Sean Culatana, Shang-En Huang, Kang Li
Dense-retrieval services must switch among embedding-prefix dimensions and index bit rates as latency, quality, and memory budgets change. Tuning a quantizer separately for each ra…
Gen2Det: Generate to Detect
Saksham Suri, Fanyi Xiao, Animesh Sinha +4
Recently diffusion models have shown improvement in synthetic image quality as well as better control in generation. We motivate and present Gen2Det, a simple modular pipeline to c…
Diversify, Don't Fine-Tune: Scaling Up Visual Recognition Training with Synthetic Images
Zhuoran Yu, Chenchen Zhu, Sean Culatana +3
Recent advances in generative deep learning have enabled the creation of high-quality synthetic images in text-to-image generation. Prior work shows that fine-tuning a pretrained d…
EgoObjects: A Large-Scale Egocentric Dataset for Fine-Grained Object Understanding
Chenchen Zhu, Fanyi Xiao, Andres Alvarado +6
Object understanding in egocentric visual data is arguably a fundamental research topic in egocentric vision. However, existing object datasets are either non-egocentric or have li…
Exploring Open-Vocabulary Semantic Segmentation without Human Labels
Jun Chen, Deyao Zhu, Guocheng Qian +6
Semantic segmentation is a crucial task in computer vision that involves segmenting images into semantically meaningful regions at the pixel level. However, existing approaches oft…
Similarity Search for Efficient Active Learning and Search of Rare Concepts
Cody Coleman, Edward Chou, Julian Katz-Samuels +7
Many active learning and search approaches are intractable for large-scale industrial settings with billions of unlabeled examples. Existing approaches search globally for the opti…