1 citations · 2 across the 10 of their papers we have counts for
5 papers · 1 filter
CAGE: Unsupervised Visual Composition and Animation for Controllable Video Generation
Aram Davtyan, Sepehr Sameni, Björn Ommer +1
The field of video generation has expanded significantly in recent years, with controllable and compositional video generation garnering considerable interest. Most methods rely on…
Multi-View Unsupervised Image Generation with Cross Attention Guidance
Llukman Cerkezi, Aram Davtyan, Sepehr Sameni +1
The growing interest in novel view synthesis, driven by Neural Radiance Field (NeRF) models, is hindered by scalability issues due to their reliance on precisely annotated multi-vi…
Spatio-Temporal Crop Aggregation for Video Representation Learning
Sepehr Sameni, Simon Jenni, Paolo Favaro
We propose Spatio-temporal Crop Aggregation for video representation LEarning (SCALE), a novel method that enjoys high scalability at both training and inference time. Our model bu…
Efficient Video Prediction via Sparsely Conditioned Flow Matching
Aram Davtyan, Sepehr Sameni, Paolo Favaro
We introduce a novel generative model for video prediction based on latent flow matching, an efficient alternative to diffusion-based models. In contrast to prior work, we keep the…
Representation Learning by Detecting Incorrect Location Embeddings
Sepehr Sameni, Simon Jenni, Paolo Favaro
In this paper, we introduce a novel self-supervised learning (SSL) loss for image representation learning. There is a growing belief that generalization in deep neural networks is…