16 citations · 49 across the 20 of their papers we have counts for
4 papers · 1 filter
A Video is Worth 10,000 Words: Training and Benchmarking with Diverse Captions for Better Long Video Retrieval
Matthew Gwilliam, Michael Cogswell, Meng Ye +3
Existing long video retrieval systems are trained and tested in the paragraph-to-video retrieval regime, where every long video is described by a single long paragraph. This neglec…
Do text-free diffusion models learn discriminative visual representations?
Soumik Mukhopadhyay, Matthew Gwilliam, Yosuke Yamaguchi +6
While many unsupervised learning models focus on one family of tasks, either generative or discriminative, we explore the possibility of a unified representation learner: a model w…
Diffusion Models Beat GANs on Image Classification
Soumik Mukhopadhyay, Matthew Gwilliam, Vatsal Agarwal +5
While many unsupervised learning models focus on one family of tasks, either generative or discriminative, we explore the possibility of a unified representation learner: a model w…
HNeRV: A Hybrid Neural Representation for Videos
Hao Chen, Matt Gwilliam, Ser-Nam Lim +1
Implicit neural representations store videos as neural networks and have performed well for various vision tasks such as video compression and denoising. With frame index or positi…