30 citations · 35 across the 5 of their papers we have counts for
5 papers
MACRO: Training-free Multi-plane Attention for Closeup Render Optimization
Nitzan Hodos, Roy Amoyal, Lior Fritz +3
Close-up rendering, zooming into a scene well beyond any training camera, is important for virtual production and interactive 3D content, yet remains an open challenge. 3D Gaussian…
Splatent: Splatting Diffusion Latents for Novel View Synthesis
Or Hirschorn, Omer Sela, Inbar Huberman-Spiegelglas +6
Radiance field representations have recently been explored in the latent space of VAEs that are commonly used by diffusion models. This direction offers efficient rendering and sea…
3D-LaneNet+: Anchor Free Lane Detection using a Semi-Local Representation
Netalee Efrat, Max Bluvstein, Shaul Oron +3
3D-LaneNet+ is a camera-based DNN method for anchor free 3D lane detection which is able to detect 3d lanes of any arbitrary topology such as splits, merges, as well as short and p…
Synthetic-to-Real Domain Adaptation for Lane Detection
Noa Garnett, Roy Uziel, Netalee Efrat +1
Accurate lane detection, a crucial enabler for autonomous driving, currently relies on obtaining a large and diverse labeled training dataset. In this work, we explore learning fro…
Semi-Local 3D Lane Detection and Uncertainty Estimation
Netalee Efrat, Max Bluvstein, Noa Garnett +3
We propose a novel camera-based DNN method for 3D lane detection with uncertainty estimation. Our method is based on a semi-local, BEV, tile representation that breaks down lanes i…