From the 1 of 5 linked papers with an AI index.
5 papers
Schrödinger's Cat: Probabilistic Representation and Prediction of Potential Scene Kinematics
Timy Phan, Jannik Wiese, Björn Ommer
The paper introduces GARFIELD, a probabilistic model that learns a structured spatio‑temporal latent representation of possible future scene motions from a single image and optiona…
Probabilistic Precipitation Nowcasting with Rectified Flow Transformers
Johannes Schusterbauer, Jannik Wiese, Nick Stracke +2
Accurate weather forecasts are essential across various domains and are safety-critical in extreme weather conditions. Compared to simulation-based forecasting, data-driven approac…
Adapting Self-Supervised Representations as a Latent Space for Efficient Generation
Ming Gui, Johannes Schusterbauer, Timy Phan +4
We introduce Representation Tokenizer (RepTok), a generative modeling framework that represents an image using a single continuous latent token obtained from self-supervised vision…
What If : Understanding Motion Through Sparse Interactions
Stefan Andreas Baumann, Nick Stracke, Timy Phan +1
Understanding the dynamics of a physical scene involves reasoning about the diverse ways it can potentially change, especially as a result of local interactions. We present the Flo…
TREAD: Token Routing for Efficient Architecture-agnostic Diffusion Training
Felix Krause, Timy Phan, Ming Gui +3
Diffusion models have emerged as the mainstream approach for visual generation. However, these models typically suffer from sample inefficiency and high training costs. Consequentl…