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20232026
most citedCinematographic Camera Diffusion Model

1 citations · 1 across the 7 of their papers we have counts for

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cs.CV2026

TAKE 85: Testing Audiovisual filmmaKer's intEnt across 85 Hours of Film

Kaishuu Shinozaki-Conefrey, Olivier Pascaud, Robin Courant +3

Films communicate through deliberate creative choices, including lighting, color, composition, editing, dialogue, music, and sound. Humans naturally interpret these signals as dire…

cs.CV2026

VERTIGO: Visual Preference Optimization for Cinematic Camera Trajectory Generation

Mengtian Li, Yuwei Lu, Feifei Li +3

Cinematic camera control relies on a tight feedback loop between director and cinematographer, where camera motion and framing are continuously reviewed and refined. Recent generat…

cs.CV2026

Bringing a Personal Point of View: Evaluating Dynamic 3D Gaussian Splatting for Egocentric Scene Reconstruction

Jan Warchocki, Xi Wang, Jonas Kulhanek +1

Egocentric video provides a unique view into human perception and interaction, with growing relevance for augmented reality, robotics, and assistive technologies. However, rapid ca…

cs.CV2024

AKiRa: Augmentation Kit on Rays for optical video generation

Xi Wang, Robin Courant, Marc Christie +1

Recent advances in text-conditioned video diffusion have greatly improved video quality. However, these methods offer limited or sometimes no control to users on camera aspects, in…

cs.CV2023

BluNF: Blueprint Neural Field

Robin Courant, Xi Wang, Marc Christie +1

Neural Radiance Fields (NeRFs) have revolutionized scene novel view synthesis, offering visually realistic, precise, and robust implicit reconstructions. While recent approaches en…