Generating novel views from limited observations requires preserving both the appearance and spatial structure of a scene. Although recent approaches exploit fine-grained geometric cues, they do not explicitly model high-level semantic and spatial properties such as object identity, attributes, and inter-object relatio...
Jahyeok Koo, Hyeonseo Yu, Seung-Ho Jang et al.· 0 citations
Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs handle single-image inputs effectively, they struggle to integrate evidence across viewpoints into a coherent 3D understanding. A growing body of work attempts to close th...
Jaewoo Jung, Hyeonseo Yu, Honggyu An et al.· 0 citations
GenRec is introduced, a multi-view flow matching model that builds the reconstruction--generation split directly into its architecture, supervision, and gradient flow, and attains the best reconstruction fidelity in observed regions while also surpassing purely generative baselines on perceptual quality in unobserved o...
Ata Çelen, Jaewoo Jung, Federico Tombari et al.· 0 citations
This work empirically finds that transferability depends on architecture-models with fully shared transformer backbone and a unified visual encoder exhibit consistent cross-task transfer, while loosely coupled designs show little or none.
Jiwon Kang, Heeji Yoon, Jaewoo Jung et al.· 1 citation
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