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cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…