← Search

Jiaxu Zhang

7 accepted papers

2026

Bridging Your Imagination with Audio-Video Generation via a Unified Director

ICML 2026poster

Existing AI-driven video creation systems typically treat script drafting and key-shot design as two disjoint tasks: the former relies on large language models, while the latter depends on image generation models. We argue that these two tasks should be unified within a single framework, as logical …

Cited by 2SourceScholar
2026

Mitigating Error Accumulation in Co-Speech Motion Generation via Global Rotation Diffusion and Multi-Level Constraints

AAAI 2026technical

Reliable co-speech motion generation requires precise motion representation and consistent structural priors across all joints. Existing generative methods typically operate on local joint rotations, which are defined hierarchically based on the skeleton structure. This leads to cumulative errors du

Cited by 0SourcePDFScholar
2025

MikuDance: Animating Character Art with Mixed Motion Dynamics

ICCV 2025poster

We propose MikuDance, a diffusion-based pipeline incorporating mixed motion dynamics to animate stylized character art. MikuDance consists of two key techniques: Mixed Motion Modeling and Mixed-Control Diffusion, to address the challenges of high-dynamic motion and reference-guidance misalignment in…

Cited by 0SourcePDFScholar
2025

OmniSVG: A Unified Scalable Vector Graphics Generation Model

NeurIPS 2025poster

Scalable Vector Graphics (SVG) is an important image format widely adopted in graphic design because of their resolution independence and editability. The study of generating high-quality SVG has continuously drawn attention from both designers and researchers in the AIGC community. However, existin…

Cited by 0SourceScholar
2025

SemTalk: Holistic Co-speech Motion Generation with Frame-level Semantic Emphasis

ICCV 2025poster

A good co-speech motion generation cannot be achieved without a careful integration of common rhythmic motion and rare yet essential semantic motion. In this work, we propose SemTalk for holistic co-speech motion generation with frame-level semantic emphasis. Our key insight is to separately learn b…

Cited by 0SourcePDFScholar
2024

TapMo: Shape-aware Motion Generation of Skeleton-free Characters

ICLR 2024poster

Previous motion generation methods are limited to the pre-rigged 3D human model, hindering their applications in the animation of various non-rigged characters. In this work, we present TapMo, a Text-driven Animation PIpeline for synthesizing Motion in a broad spectrum of skeleton-free 3D characters…

Cited by 11SourcePDFScholar
2023

Skinned Motion Retargeting With Residual Perception of Motion Semantics & Geometry

CVPR 2023poster

A good motion retargeting cannot be reached without reasonable consideration of source-target differences on both the skeleton and shape geometry levels. In this work, we propose a novel Residual RETargeting network (R2ET) structure, which relies on two neural modification modules, to adjust the sou…