4 citations · 7 across the 5 of their papers we have counts for
5 papers
Unsupervised Feature Learning with Emergent Data-Driven Prototypicality
Yunhui Guo, Youren Zhang, Yubei Chen +1
Given an image set without any labels, our goal is to train a model that maps each image to a point in a feature space such that, not only proximity indicates visual similarity, bu…
The Audio-Visual BatVision Dataset for Research on Sight and Sound
Amandine Brunetto, Sascha Hornauer, Stella X. Yu +1
Vision research showed remarkable success in understanding our world, propelled by datasets of images and videos. Sensor data from radar, LiDAR and cameras supports research in rob…
Unsupervised Hierarchical Semantic Segmentation with Multiview Cosegmentation and Clustering Transformers
Tsung-Wei Ke, Jyh-Jing Hwang, Yunhui Guo +2
Unsupervised semantic segmentation aims to discover groupings within and across images that capture object and view-invariance of a category without external supervision. Grouping…
CO-SNE: Dimensionality Reduction and Visualization for Hyperbolic Data
Yunhui Guo, Haoran Guo, Stella Yu
Hyperbolic space can naturally embed hierarchies that often exist in real-world data and semantics. While high-dimensional hyperbolic embeddings lead to better representations, mos…
Unsupervised Selective Labeling for More Effective Semi-Supervised Learning
Xudong Wang, Long Lian, Stella X. Yu
Given an unlabeled dataset and an annotation budget, we study how to selectively label a fixed number of instances so that semi-supervised learning (SSL) on such a partially labele…