RayZer: A Self-supervised Large View Synthesis Model
Learns 3D scene reconstruction from images without known cameras or 3D supervision. Disentangled camera and scene representations use ray structure and view reconstruction to learn from 2D images.
Overview
Learns 3D scene reconstruction from images without known cameras or 3D supervision. Disentangled camera and scene representations use ray structure and view reconstruction to learn from 2D images.
Learns 3D scene reconstruction from images without known cameras or 3D supervision. Disentangled camera and scene representations use ray structure and view reconstruction to learn from 2D images.
When reading the original paper, identify its problem, inputs, outputs, and methodological assumptions.
Learns 3D scene reconstruction from images without known cameras or 3D supervision. Disentangled camera and scene representations use ray structure and view reconstruction to learn from 2D images.
Check the baselines, datasets, evaluation protocol, and ablations in the original paper. This directory overview does not provide an independent evaluation or experimental results table.
References
ID: iccv-2025-rayzer · Last verified:
