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cs.CV2026
Steering Visual Generation in Unified Multimodal Models with Understanding Supervision
Zeyu Liu, Zanlin Ni, Yang Yue +5
Unified multimodal models are envisioned to bridge the gap between understanding and generation. Yet, to achieve competitive performance, state-of-the-art models adopt largely deco…
cs.CV2024
DragAnything: Motion Control for Anything using Entity Representation
Weijia Wu, Zhuang Li, Yuchao Gu +7
We introduce DragAnything, which utilizes a entity representation to achieve motion control for any object in controllable video generation. Comparison to existing motion control m…
cs.CV2023
Paragraph-to-Image Generation with Information-Enriched Diffusion Model
Weijia Wu, Zhuang Li, Yefei He +6
Text-to-image (T2I) models have recently experienced rapid development, achieving astonishing performance in terms of fidelity and textual alignment capabilities. However, given a…