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cs.CV2026
Can Learning to Answer Spatial Questions Improve Novel-View Generation?
Jahyeok Koo, Hyeonseo Yu, Seungho Jang +4
Generating novel views from limited observations requires preserving both the appearance and spatial structure of a scene. Although recent approaches exploit fine-grained geometric…
cs.CV2026
Transferability Between Understanding and Generation in Unified Multimodal Models
Jiwon Kang, Heeji Yoon, Jaewoo Jung +5
Unified Multimodal Models (UMMs) integrate image understanding and generation within a single architecture, yet how the two tasks interact remains understudied. We investigate $\bo…
cs.CV2026
APPLE: Attribute-Preserving Pseudo-Labeling for Diffusion-Based Face Swapping
Jiwon Kang, Yeji Choi, JoungBin Lee +6
Face swapping aims to transfer the identity of a source face onto a target face while preserving target-specific attributes such as pose, expression, lighting, skin tone, and makeu…