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Integrating View Conditions for Image Synthesis

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arxiv 2310.16002 v3 pith:KZBNJ5KI submitted 2023-10-24 cs.CV

classification cs.CV
keywords imageeditingframeworksynthesischallengeexistingmodificationsobject
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In the field of image processing, applying intricate semantic modifications within existing images remains an enduring challenge. This paper introduces a pioneering framework that integrates viewpoint information to enhance the control of image editing tasks, especially for interior design scenes. By surveying existing object editing methodologies, we distill three essential criteria -- consistency, controllability, and harmony -- that should be met for an image editing method. In contrast to previous approaches, our framework takes the lead in satisfying all three requirements for addressing the challenge of image synthesis. Through comprehensive experiments, encompassing both quantitative assessments and qualitative comparisons with contemporary state-of-the-art methods, we present compelling evidence of our framework's superior performance across multiple dimensions. This work establishes a promising avenue for advancing image synthesis techniques and empowering precise object modifications while preserving the visual coherence of the entire composition.

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Cited by 1 Pith paper

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  1. Track Any Anomalous Object: A Granular Video Anomaly Detection Pipeline

    cs.CV 2025-06 conditional novelty 5.0 of 10

    TAO pipelines object-centric anomaly scores into SAM2 prompts with a temporal consistency filter to obtain pixel-level anomaly segmentation and tracking.

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