33 citations · 50 across the 5 of their papers we have counts for
6 papers · 1 filter
V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning
Lorenzo Mur-Labadia, Matthew Muckley, Amir Bar +6
We present V-JEPA 2.1, a family of self-supervised models that learn dense, high-quality visual representations for both images and videos while retaining strong global scene under…
Towards image compression with perfect realism at ultra-low bitrates
Marlène Careil, Matthew J. Muckley, Jakob Verbeek +1
Image codecs are typically optimized to trade-off bitrate \vs distortion metrics. At low bitrates, this leads to compression artefacts which are easily perceptible, even when train…
Training-free Linear Image Inverses via Flows
Ashwini Pokle, Matthew J. Muckley, Ricky T. Q. Chen +1
Solving inverse problems without any training involves using a pretrained generative model and making appropriate modifications to the generation process to avoid finetuning of the…
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction
Anuroop Sriram, Matthew Muckley, Koustuv Sinha +7
The rapid spread of COVID-19 cases in recent months has strained hospital resources, making rapid and accurate triage of patients presenting to emergency departments a necessity. M…
Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition
Zizhao Zhang, Adriana Romero, Matthew J. Muckley +3
The goal of MRI reconstruction is to restore a high fidelity image from partially observed measurements. This partial view naturally induces reconstruction uncertainty that can onl…
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
Jure Zbontar, Florian Knoll, Anuroop Sriram +24
Accelerating Magnetic Resonance Imaging (MRI) by taking fewer measurements has the potential to reduce medical costs, minimize stress to patients and make MRI possible in applicati…