Next Week: CV-DL Seminar – Leo Segre | 3D-Consistent Representations
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Naaman Kopty
May 10, 2026, 7:14:34 AMMay 10
to 'Google Groups' via CV-DL Seminar – University of Haifa
Dear all,
You are invited to attend the next talk in the CV-DL Seminar Series.
Leo Segre
TAU
TAU
Sunday, May 17, 2026
11:15-12:30
Room 508, Amir Building
11:15-12:30
Room 508, Amir Building
Title:
3D-Consistent Representations
3D-Consistent Representations
Abstract:
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.
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.
Bio:
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.
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.
We look forward to seeing you there.
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