10 citations · 11 across the 7 of their papers we have counts for
10 papers · 1 filter
Multiplayer Interactive World Models with Representation Autoencoders
Anthony Hu, Václav Volhejn, Adrien Ramanana Rahary +24
We introduce the first multiplayer world model for highly dynamic environments governed by complex physical interactions. Whereas single-player world models treat the other agents…
Visual-Word Tokenizer: Beyond Fixed Sets of Tokens in Vision Transformers
Leonidas Gee, Wing Yan Li, Viktoriia Sharmanska +1
The cost of deploying vision transformers increasingly represents a barrier to wider industrial adoption. Existing compression techniques require additional end-to-end fine-tuning…
Distribution Matching for Multi-Task Learning of Classification Tasks: a Large-Scale Study on Faces & Beyond
Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
Multi-Task Learning (MTL) is a framework, where multiple related tasks are learned jointly and benefit from a shared representation space, or parameter transfer. To provide suffici…
Okapi: Generalising Better by Making Statistical Matches Match
Myles Bartlett, Sara Romiti, Viktoriia Sharmanska +1
We propose Okapi, a simple, efficient, and general method for robust semi-supervised learning based on online statistical matching. Our method uses a nearest-neighbours-based match…
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study
Dimitrios Kollias, Viktoriia Sharmanska, Stefanos Zafeiriou
Multi-Task Learning has emerged as a methodology in which multiple tasks are jointly learned by a shared learning algorithm, such as a DNN. MTL is based on the assumption that the…
Head2HeadFS: Video-based Head Reenactment with Few-shot Learning
Michail Christos Doukas, Mohammad Rami Koujan, Viktoriia Sharmanska +1
Over the past years, a substantial amount of work has been done on the problem of facial reenactment, with the solutions coming mainly from the graphics community. Head reenactment…