activity
20152024
most citedYou Only Need Adversarial Supervision for Semantic Image Synthesis

70 citations · 308 across the 22 of their papers we have counts for

collaborators

24 papers

cs.CV2024

Label-free Neural Semantic Image Synthesis

Jiayi Wang, Kevin Alexander Laube, Yumeng Li +4

Recent work has shown great progress in integrating spatial conditioning to control large, pre-trained text-to-image diffusion models. Despite these advances, existing methods desc…

cs.LG2024

ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections

Massimo Bini, Karsten Roth, Zeynep Akata +1

Parameter-efficient finetuning (PEFT) has become ubiquitous to adapt foundation models to downstream task requirements while retaining their generalization ability. However, the am…

cs.CV2024★ 1 cited

VSTAR: Generative Temporal Nursing for Longer Dynamic Video Synthesis

Yumeng Li, William Beluch, Margret Keuper +2

Despite tremendous progress in the field of text-to-video (T2V) synthesis, open-sourced T2V diffusion models struggle to generate longer videos with dynamically varying and evolvin…

cs.CV2024

Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive

Yumeng Li, Margret Keuper, Dan Zhang +1

Despite the recent advances in large-scale diffusion models, little progress has been made on the layout-to-image (L2I) synthesis task. Current L2I models either suffer from poor e…

cs.CV2023

Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain Generalization

Yumeng Li, Dan Zhang, Margret Keuper +1

The generalization with respect to domain shifts, as they frequently appear in applications such as autonomous driving, is one of the remaining big challenges for deep learning mod…

cs.CV2023★ 1 cited

Divide & Bind Your Attention for Improved Generative Semantic Nursing

Yumeng Li, Margret Keuper, Dan Zhang +1

Emerging large-scale text-to-image generative models, e.g., Stable Diffusion (SD), have exhibited overwhelming results with high fidelity. Despite the magnificent progress, current…