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Wen Li*

3 accepted papers

2024

Learning Semantic Latent Directions for Accurate and Controllable Human Motion Prediction

ECCV 2024poster

"In the realm of stochastic human motion prediction (SHMP), researchers have often turned to generative models like GANS, VAEs and diffusion models. However, most previous approaches have struggled to accurately predict motions that are both realistic and coherent with past motion due to a lack of g…

2024

Powerful and Flexible: Personalized Text-to-Image Generation via Reinforcement Learning

ECCV 2024poster

"Personalized text-to-image models allow users to generate varied styles of images (specified with a sentence) for an object (specified with a set of reference images). While remarkable results have been achieved using diffusion-based generation models, the visual structure and details of the object…

2024

StyleTokenizer: Defining Image Style by a Single Instance for Controlling Diffusion Models

ECCV 2024poster

"Despite the burst of innovative methods for controlling the diffusion process, effectively controlling image styles in text-to-image generation remains a challenging task. Many adapter-based methods impose image representation conditions on the denoising process to accomplish image control. However…