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Research questionHow can novel-view synthesis represent continuous 3D scenes with less capacity and optimization than NeRFs?Novel-view synthesis infers a continuous volumetric scene from posed 2D images. NeRF-style representations can require substantial model capacity and intensive optimization to produce new views.
AI
Computer Vision
Image & Video Processing
Machine Learning
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Latest papersRecent research connected to this question, newest first.Quantum Implicit Neural Representations for Novel View SynthesisThe source studies 3D-QISR, a hybrid quantum-classical radiance-field system using parameterized quantum circuits in place of a classical NeRF backbone while retaining standard volumetric rendering. Evidence comes from moderate-resolution benchmarks on simulated quantum hardware; the reported architectures use fewer than half the trainable parameters of the classical baselines.research paper · Sep 3, 2026
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How can novel-view synthesis use mirror reflections to generate consistent views and recover hidden scene structure?How can sparse-view 3D scene representations avoid cross-view artifacts without costly per-scene reconstruction?How can sparse-view novel-view synthesis maintain geometric and temporal consistency along a camera trajectory?How can camera viewpoints be optimized for novel-view synthesis when reflections and fine textures change with viewpoint?