19 citations · 27 across the 20 of their papers we have counts for
7 papers · 1 filter
VISReg: Variance-Invariance-Sketching Regularization for JEPA training
Haiyu Wu, Randall Balestriero, Morgan Levine
Self-supervised learning methods prevent embedding collapse via modeling heuristics or explicit regularization of the embedding space. Among the latter, VICReg decomposes regulariz…
MapSAM2: Adapting SAM2 for Automatic Segmentation of Historical Map Images and Time Series
Xue Xia, Randall Balestriero, Tao Zhang +4
Historical maps are unique and valuable archives that document geographic features across different time periods. However, automated analysis of historical map images remains a sig…
Beyond and Free from Diffusion: Invertible Guided Consistency Training
Chia-Hong Hsu, Shiu-hong Kao, Randall Balestriero
Guidance in image generation steers models towards higher-quality or more targeted outputs, typically achieved in Diffusion Models (DMs) via Classifier-free Guidance (CFG). However…
Beyond [cls]: Exploring the true potential of Masked Image Modeling representations
Marcin Przewięźlikowski, Randall Balestriero, Wojciech Jasiński +2
Masked Image Modeling (MIM) has emerged as a promising approach for Self-Supervised Learning (SSL) of visual representations. However, the out-of-the-box performance of MIMs is typ…
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps
Xue Xia, Randall Balestriero, Tao Zhang +1
Tracking geographic entities from historical maps, such as buildings, offers valuable insights into cultural heritage, urbanization patterns, environmental changes, and various his…
Self-Supervised Anomaly Detection in the Wild: Favor Joint Embeddings Methods
Daniel Otero, Rafael Mateus, Randall Balestriero
Accurate anomaly detection is critical in vision-based infrastructure inspection, where it helps prevent costly failures and enhances safety. Self-Supervised Learning (SSL) offers…
GPS-SSL: Guided Positive Sampling to Inject Prior Into Self-Supervised Learning
Aarash Feizi, Randall Balestriero, Adriana Romero-Soriano +1
We propose Guided Positive Sampling Self-Supervised Learning (GPS-SSL), a general method to inject a priori knowledge into Self-Supervised Learning (SSL) positive samples selection…