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cs.CV2022
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…
cs.CV2022★ 1 cited
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…
cs.CV2022★ 1 cited
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…