3 papers
cs.CV2026
ISAC: Training-Free Instance-to-Semantic Attention Control for Multi-Instance Generation
Sanghyun Jo, Wooyeol Lee, Ziseok Lee +3
Recent open-weight text-to-image (T2I) diffusion models still struggle with multi-instance prompts, often omitting or merging instances and mixing semantics among similar objects.…
cs.AI2026
On the Collapse of Generative Paths: A Criterion and Correction for Diffusion Steering
Ziseok Lee, Minyeong Hwang, Wooyeol Lee +6
Inference-time steering adapts pretrained diffusion and flow models to new tasks without retraining, often utilizing ratio-of-densities constructions that reweight time-indexed mar…
cs.CV2026
TRACE: Your Diffusion Model is Secretly an Instance Edge Detector
Sanghyun Jo, Ziseok Lee, Wooyeol Lee +3
High-quality instance and panoptic segmentation has traditionally relied on dense instance-level annotations such as masks, boxes, or points, which are costly, inconsistent, and di…