34 citations · 145 across the 36 of their papers we have counts for
37 papers · 1 filter
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
FlowAct-R1: Towards Interactive Humanoid Video Generation
Lizhen Wang, Yongming Zhu, Zhipeng Ge +15
Interactive humanoid video generation aims to synthesize lifelike visual agents that can engage with humans through continuous and responsive video. Despite recent advances in vide…
OmniHuman-1.5: Instilling an Active Mind in Avatars via Cognitive Simulation
Jianwen Jiang, Weihong Zeng, Zerong Zheng +6
Existing video avatar models can produce fluid human animations, yet they struggle to move beyond mere physical likeness to capture a character's authentic essence. Their motions t…
DreamVVT: Mastering Realistic Video Virtual Try-On in the Wild via a Stage-Wise Diffusion Transformer Framework
Tongchun Zuo, Zaiyu Huang, Shuliang Ning +7
Video virtual try-on (VVT) technology has garnered considerable academic interest owing to its promising applications in e-commerce advertising and entertainment. However, most exi…
AlignHuman: Improving Motion and Fidelity via Timestep-Segment Preference Optimization for Audio-Driven Human Animation
Chao Liang, Jianwen Jiang, Wang Liao +4
Recent advancements in human video generation and animation tasks, driven by diffusion models, have achieved significant progress. However, expressive and realistic human animation…
DreamActor-H1: High-Fidelity Human-Product Demonstration Video Generation via Motion-designed Diffusion Transformers
Lizhen Wang, Zhurong Xia, Tianshu Hu +6
In e-commerce and digital marketing, generating high-fidelity human-product demonstration videos is important for effective product presentation. However, most existing frameworks…
InterActHuman: Multi-Concept Human Animation with Layout-Aligned Audio Conditions
Zhenzhi Wang, Jiaqi Yang, Jianwen Jiang +7
End-to-end human animation with rich multi-modal conditions, e.g., text, image and audio has achieved remarkable advancements in recent years. However, most existing methods could…
OmniHuman-1: Rethinking the Scaling-Up of One-Stage Conditioned Human Animation Models
Gaojie Lin, Jianwen Jiang, Jiaqi Yang +2
End-to-end human animation, such as audio-driven talking human generation, has undergone notable advancements in the recent few years. However, existing methods still struggle to s…
MeshAvatar: Learning High-quality Triangular Human Avatars from Multi-view Videos
Yushuo Chen, Zerong Zheng, Zhe Li +2
We present a novel pipeline for learning high-quality triangular human avatars from multi-view videos. Recent methods for avatar learning are typically based on neural radiance fie…
GPHM: Gaussian Parametric Head Model for Monocular Head Avatar Reconstruction
Yuelang Xu, Zhaoqi Su, Qingyao Wu +1
Creating high-fidelity 3D human head avatars is crucial for applications in VR/AR, digital human, and film production. Recent advances have leveraged morphable face models to gener…
LayGA: Layered Gaussian Avatars for Animatable Clothing Transfer
Siyou Lin, Zhe Li, Zhaoqi Su +3
Animatable clothing transfer, aiming at dressing and animating garments across characters, is a challenging problem. Most human avatar works entangle the representations of the hum…
Human4DiT: 360-degree Human Video Generation with 4D Diffusion Transformer
Ruizhi Shao, Youxin Pang, Zerong Zheng +2
We present a novel approach for generating 360-degree high-quality, spatio-temporally coherent human videos from a single image. Our framework combines the strengths of diffusion t…
HHAvatar: Gaussian Head Avatar with Dynamic Hairs
Zhanfeng Liao, Yuelang Xu, Zhe Li +6
Creating high-fidelity 3D head avatars has always been a research hotspot, but it remains a great challenge under lightweight sparse view setups. In this paper, we propose HHAvatar…
SpeechAct: Towards Generating Whole-body Motion from Speech
Jinsong Zhang, Minjie Zhu, Yuxiang Zhang +2
This paper addresses the problem of generating whole-body motion from speech. Despite great successes, prior methods still struggle to produce reasonable and diverse whole-body mot…
Animatable and Relightable Gaussians for High-fidelity Human Avatar Modeling
Zhe Li, Yipengjing Sun, Zerong Zheng +3
Modeling animatable human avatars from RGB videos is a long-standing and challenging problem. Recent works usually adopt MLP-based neural radiance fields (NeRF) to represent 3D hum…
Leveraging Intrinsic Properties for Non-Rigid Garment Alignment
Siyou Lin, Boyao Zhou, Zerong Zheng +2
We address the problem of aligning real-world 3D data of garments, which benefits many applications such as texture learning, physical parameter estimation, generative modeling of…
PoseVocab: Learning Joint-structured Pose Embeddings for Human Avatar Modeling
Zhe Li, Zerong Zheng, Yuxiao Liu +2
Creating pose-driven human avatars is about modeling the mapping from the low-frequency driving pose to high-frequency dynamic human appearances, so an effective pose encoding meth…
AvatarReX: Real-time Expressive Full-body Avatars
Zerong Zheng, Xiaochen Zhao, Hongwen Zhang +2
We present AvatarReX, a new method for learning NeRF-based full-body avatars from video data. The learnt avatar not only provides expressive control of the body, hands and the face…
Control4D: Efficient 4D Portrait Editing with Text
Ruizhi Shao, Jingxiang Sun, Cheng Peng +4
We introduce Control4D, an innovative framework for editing dynamic 4D portraits using text instructions. Our method addresses the prevalent challenges in 4D editing, notably the i…
CloSET: Modeling Clothed Humans on Continuous Surface with Explicit Template Decomposition
Hongwen Zhang, Siyou Lin, Ruizhi Shao +5
Creating animatable avatars from static scans requires the modeling of clothing deformations in different poses. Existing learning-based methods typically add pose-dependent deform…
Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Rendering
Ruizhi Shao, Zerong Zheng, Hanzhang Tu +3
We present Tensor4D, an efficient yet effective approach to dynamic scene modeling. The key of our solution is an efficient 4D tensor decomposition method so that the dynamic scene…
DiffuStereo: High Quality Human Reconstruction via Diffusion-based Stereo Using Sparse Cameras
Ruizhi Shao, Zerong Zheng, Hongwen Zhang +2
We propose DiffuStereo, a novel system using only sparse cameras (8 in this work) for high-quality 3D human reconstruction. At its core is a novel diffusion-based stereo module, wh…
Learning Implicit Templates for Point-Based Clothed Human Modeling
Siyou Lin, Hongwen Zhang, Zerong Zheng +2
We present FITE, a First-Implicit-Then-Explicit framework for modeling human avatars in clothing. Our framework first learns implicit surface templates representing the coarse clot…
AvatarCap: Animatable Avatar Conditioned Monocular Human Volumetric Capture
Zhe Li, Zerong Zheng, Hongwen Zhang +2
To address the ill-posed problem caused by partial observations in monocular human volumetric capture, we present AvatarCap, a novel framework that introduces animatable avatars in…