2 citations · 2 across the 6 of their papers we have counts for
6 papers
CHARM: Control-point-based 3D Anime Hairstyle Auto-Regressive Modeling
Yuze He, Yanning Zhou, Wang Zhao +6
We present CHARM, a novel parametric representation and generative framework for anime hairstyle modeling. While traditional hair modeling methods focus on realistic hair using str…
Think in Games: Learning to Reason in Games via Reinforcement Learning with Large Language Models
Yi Liao, Yu Gu, Yuan Sui +5
Large language models (LLMs) excel at complex reasoning tasks such as mathematics and coding, yet they frequently struggle with simple interactive tasks that young children perform…
ProGDF: Progressive Gaussian Differential Field for Controllable and Flexible 3D Editing
Yian Zhao, Wanshi Xu, Yang Wu +3
3D editing plays a crucial role in editing and reusing existing 3D assets, thereby enhancing productivity. Recently, 3DGS-based methods have gained increasing attention due to thei…
GUESS:GradUally Enriching SyntheSis for Text-Driven Human Motion Generation
Xuehao Gao, Yang Yang, Zhenyu Xie +3
In this paper, we propose a novel cascaded diffusion-based generative framework for text-driven human motion synthesis, which exploits a strategy named GradUally Enriching SyntheSi…
Act As You Wish: Fine-Grained Control of Motion Diffusion Model with Hierarchical Semantic Graphs
Peng Jin, Yang Wu, Yanbo Fan +3
Most text-driven human motion generation methods employ sequential modeling approaches, e.g., transformer, to extract sentence-level text representations automatically and implicit…
Speech2Lip: High-fidelity Speech to Lip Generation by Learning from a Short Video
Xiuzhe Wu, Pengfei Hu, Yang Wu +6
Synthesizing realistic videos according to a given speech is still an open challenge. Previous works have been plagued by issues such as inaccurate lip shape generation and poor im…