2 citations · 3 across the 11 of their papers we have counts for
9 papers · 1 filter
GDPO-Listener: Expressive Interactive Head Generation via Auto-Regressive Flow Matching and Group reward-Decoupled Policy Optimization
Zhangyu Jin, Maksim Siniukov, Deuksin Kwon +2
Generating realistic 3D head motion for dyadic interactions is a significant challenge in virtual human synthesis. While recent methods achieve impressive results with speaking hea…
HairWeaver: Few-Shot Photorealistic Hair Motion Synthesis with Sim-to-Real Guided Video Diffusion
Di Chang, Ji Hou, Aljaz Bozic +8
We present HairWeaver, a diffusion-based pipeline that animates a single human image with realistic and expressive hair dynamics. While existing methods successfully control body p…
ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid Motions
Di Chang, Mingdeng Cao, Yichun Shi +7
Editing images with instructions to reflect non-rigid motions, camera viewpoint shifts, object deformations, human articulations, and complex interactions, poses a challenging yet…
Face-LLaVA: Facial Expression and Attribute Understanding through Instruction Tuning
Ashutosh Chaubey, Xulang Guan, Mohammad Soleymani
The human face plays a central role in social communication, necessitating the use of performant computer vision tools for human-centered applications. We propose Face-LLaVA, a mul…
DiTaiListener: Controllable High Fidelity Listener Video Generation with Diffusion
Maksim Siniukov, Di Chang, Minh Tran +3
Generating naturalistic and nuanced listener motions for extended interactions remains an open problem. Existing methods often rely on low-dimensional motion codes for facial behav…
X-Dyna: Expressive Dynamic Human Image Animation
Di Chang, Hongyi Xu, You Xie +12
We introduce X-Dyna, a novel zero-shot, diffusion-based pipeline for animating a single human image using facial expressions and body movements derived from a driving video, that g…
MagicPose4D: Crafting Articulated Models with Appearance and Motion Control
Hao Zhang, Di Chang, Fang Li +2
With the success of 2D and 3D visual generative models, there is growing interest in generating 4D content. Existing methods primarily rely on text prompts to produce 4D content, b…
Dyadic Interaction Modeling for Social Behavior Generation
Minh Tran, Di Chang, Maksim Siniukov +1
Human-human communication is like a delicate dance where listeners and speakers concurrently interact to maintain conversational dynamics. Hence, an effective model for generating…
MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion
Di Chang, Yichun Shi, Quankai Gao +7
In this work, we propose MagicPose, a diffusion-based model for 2D human pose and facial expression retargeting. Specifically, given a reference image, we aim to generate a person'…