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New AI model learns joint distribution of videos and camera trajectories

Researchers have developed a novel Video Diffusion Model called Rays as Pixels, which learns a joint distribution of videos and camera trajectories. This model is the first to predict camera poses and generate videos from novel viewpoints within a single framework. By representing cameras as ray pixels (raxels) in the same latent space as video frames, the model can perform tasks such as predicting camera trajectories, generating video from input images along a defined path, and jointly synthesizing video and trajectory. AI

IMPACT Introduces a unified approach for video and camera trajectory learning, potentially improving scene understanding and novel view synthesis.

RANK_REASON This is a research paper describing a novel AI model and its capabilities. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New AI model learns joint distribution of videos and camera trajectories

COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Wonbong Jang, Shikun Liu, Soubhik Sanyal, Juan Camilo Perez, Kam Woh Ng, Sanskar Agrawal, Juan-Manuel Perez-Rua, Yiannis Douratsos, Tao Xiang ·

    Rays as Pixels: Learning A Joint Distribution of Videos and Camera Trajectories

    arXiv:2604.09429v4 Announce Type: replace-cross Abstract: Recovering camera parameters from images and rendering scenes from novel viewpoints have been treated as separate tasks in computer vision and graphics. This separation breaks down when image coverage is sparse or poses ar…