Music generation has advanced markedly through multimodal deep learning, enabling models to synthesize audio from text and, more recently, from images. However,...
The ever increasing intensity and number of disasters make even more difficult the work of First Responders (FRs). Artificial intelligence and robotics solution...
Recent advances in multimodal large language models (MLLMs) have shown great potential for extending vision-language reasoning to professional tool-based image ...
Implicit Neural Representations (INRs) have recently demonstrated impressive performance for video compression. However, since a separate INR must be overfit fo...
Visual loco-manipulation of arbitrary objects in the wild with humanoid robots requires accurate end-effector (EE) control and a generalizable understanding of ...
Vision-language models (VLMs) aim to reason by jointly leveraging visual and textual modalities. While allocating additional inference-time computation has prov...
A core aspect of human perception is situated awareness, the ability to relate ourselves to the surrounding physical environment and reason over possible action...
Time-series anomaly detection (TSAD) requires identifying both immediate Point Anomalies and long-range Context Anomalies. However, existing foundation models f...
High-definition (HD) maps are crucial to autonomous driving, providing structured representations of road elements to support navigation and planning. However, ...
Adversarial diffusion and diffusion-inversion methods have advanced unpaired image-to-image translation, but each faces key limitations. Adversarial approaches ...
Humans can infer material characteristics of objects from their visual appearance, and this ability extends to artistic depictions, where similar perceptual str...
Acknowledgements We would like to thank our mentors, Asaf Nisani and Yoav Lebendiker, for their guidance throughout the project. Dataset Preparation Our projec...
