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cs.CV2025
Locality-aware Concept Bottleneck Model
Sujin Jeon, Hyundo Lee, Eungseo Kim +3
Concept bottleneck models (CBMs) are inherently interpretable models that make predictions based on human-understandable visual cues, referred to as concepts. As obtaining dense co…
cs.CV2025
Towards Spatially Consistent Image Generation: On Incorporating Intrinsic Scene Properties into Diffusion Models
Hyundo Lee, Suhyung Choi, Inwoo Hwang +1
Image generation models trained on large datasets can synthesize high-quality images but often produce spatially inconsistent and distorted images due to limited information about…
cs.CV2025
OBSER: Object-Based Sub-Environment Recognition for Zero-Shot Environmental Inference
Won-Seok Choi, Dong-Sig Han, Suhyung Choi +2
We present the Object-Based Sub-Environment Recognition (OBSER) framework, a novel Bayesian framework that infers three fundamental relationships between sub-environments and their…