18 citations · 34 across the 5 of their papers we have counts for
6 papers
Multi-subject Open-set Personalization in Video Generation
Tsai-Shien Chen, Aliaksandr Siarohin, Willi Menapace +7
Video personalization methods allow us to synthesize videos with specific concepts such as people, pets, and places. However, existing methods often focus on limited domains, requi…
AV-Link: Temporally-Aligned Diffusion Features for Cross-Modal Audio-Video Generation
Moayed Haji-Ali, Willi Menapace, Aliaksandr Siarohin +5
We propose AV-Link, a unified framework for Video-to-Audio (A2V) and Audio-to-Video (A2V) generation that leverages the activations of frozen video and audio diffusion models for t…
NIRVANA: Neural Implicit Representations of Videos with Adaptive Networks and Autoregressive Patch-wise Modeling
Shishira R Maiya, Sharath Girish, Max Ehrlich +6
Implicit Neural Representations (INR) have recently shown to be powerful tool for high-quality video compression. However, existing works are limiting as they do not explicitly exp…
Revisiting Neighborhood-based Link Prediction for Collaborative Filtering
Hao-Ming Fu, Patrick Poirson, Kwot Sin Lee +1
Collaborative filtering (CF) is one of the most successful and fundamental techniques in recommendation systems. In recent years, Graph Neural Network (GNN)-based CF models, such a…
InfoMax-GAN: Improved Adversarial Image Generation via Information Maximization and Contrastive Learning
Kwot Sin Lee, Ngoc-Trung Tran, Ngai-Man Cheung
While Generative Adversarial Networks (GANs) are fundamental to many generative modelling applications, they suffer from numerous issues. In this work, we propose a principled fram…
Mimicry: Towards the Reproducibility of GAN Research
Kwot Sin Lee, Christopher Town
Advancing the state of Generative Adversarial Networks (GANs) research requires one to make careful and accurate comparisons with existing works. Yet, this is often difficult to ac…