Roman Christian Bachmann

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Different users find different images generated for the same prompt desirable. This gives rise to personalized image generation which involves creating images aligned with an individual’s visual preference. Current generative models are, however, tuned to ...

The Abstraction is at the heart of sketching due to the simple and minimal nature of line drawings. Abstraction entails identifying the essential visual properties of an object or scene, which requires semantic understanding and prior knowledge of high-lev ...

We propose a pre-training strategy called Multi-modal Multi-task Masked Autoencoders (MultiMAE). It differs from standard Masked Autoencoding in two key aspects: I) it can optionally accept additional modalities of information in the input besides the RGB ...

Effectively localizing an agent in a realistic, noisy setting is crucial for many embodied vision tasks. Visual Odometry (VO) is a practical substitute for unreliable GPS and compass sensors, especially in indoor environments. While SLAM-based methods show ...

Current machine learning models for vision are often highly specialized and limited to a single modality and task. In contrast, recent large language models exhibit a wide range of capabilities, hinting at a possibility for similarly versatile models in co ...

Roman Christian Bachmann

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ViPer: Visual Personalization of Generative Models via Individual Preference Learning

CLIPasso: Semantically-Aware Object Sketching

MultiMAE: Multi-modal Multi-task Masked Autoencoders

Modality-invariant Visual Odometry for Embodied Vision

4M: Massively Multimodal Masked Modeling