סמינר: Pixel Club
Understanding Scenes as 3D-Consistent Representations
Date:
December,16,2025
Start Time:
11:30 - 12:30
Location:
506, Zisapel Building
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Lecturer:
Leo Segre
Research Areas:
| In this talk, we explore methods for understanding and manipulating 3D scenes through consistent geometric and photometric representations. We begin with VF-NeRF, an approach for NeRF registration that aligns scenes using visibility-aware novel views. We then describe Optimize the Unseen, a method that leverages a free-space prior to improve NeRF reconstructions by removing artifacts in regions with limited observations. Next, we introduce a frequency-aware decomposition for 3D Gaussian Splatting, enabling progressive rendering, foveated visualization, and efficient interaction with complex scenes. Finally, we present Multi-View Foundation Models, which incorporate multi-view consistency into vision foundation models to produce 3D-aware representations directly from 2D features. Together, these contributions highlight how visibility, frequency structure, and multi-view reasoning can lead to more expressive and reliable 3D scene representations. |
| Leo Segre is a PhD candidate at Tel Aviv University, supervised by Prof. Shai Avidan. His research centers on understanding how 3D structure, visibility, and multi-view relationships can be used to improve learned representations. He works on neural scene representations and 3D-aware vision models, with an emphasis on algorithms that combine geometric constraints with data-driven learning.
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