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ORCA: Occlusion-Aware Refinement and Completion for Novel View Synthesis

Paper recorded by Signals 4 on 2026-09-15 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.CV · 计算机视觉 · first seen 2026-09-16

Abstract

Novel-view synthesis from a single image is a fundamentally ambiguous problem. As the camera moves away from the input viewpoint, previously hidden regions become visible, exposing missing geometry and holes in the reconstructed scene. Existing methods often rely on generative models to complete such regions. However, many of these artifacts are small gaps near depth boundaries and do not require

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#30 most recent of 237 cs.CV papers we have recorded · ↑ newer: Video-Based Markerless Motion Capture for Clinical and Rehabilitation · ↓ older: BrainFocus: EEG-Guided ROI Selection for Efficient Vision-Language Mod
Cite this page: ORCA: Occlusion-Aware Refinement and Completion for Novel View Synthesis: the #30 most recent of 237 cs.CV papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/orca-occlusion-aware-refinement-and-completion-for-novel-view-synthesis.html
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