158 citations · 734 across the 53 of their papers we have counts for
53 papers
Mix3R: Mixing Feed-forward Reconstruction and Generative 3D Priors for Joint Multi-view Aligned 3D Reconstruction and Pose Estimation
Siyou Lin, Zhou Xue, Hongwen Zhang +4
Recent trends in sparse-view 3D reconstruction have taken two different paths: feed-forward reconstruction that predicts pixel-aligned point maps without a complete geometry, and g…
SharpTimeGS: Sharp and Stable Dynamic Gaussian Splatting via Lifespan Modulation
Zhanfeng Liao, Jiajun Zhang, Hanzhang Tu +4
Novel view synthesis of dynamic scenes is fundamental to achieving photorealistic 4D reconstruction and immersive visual experiences. Recent progress in Gaussian-based representati…
DevilSight: Augmenting Monocular Human Avatar Reconstruction through a Virtual Perspective
Yushuo Chen, Ruizhi Shao, Youxin Pang +4
We present a novel framework to reconstruct human avatars from monocular videos. Recent approaches have struggled either to capture the fine-grained dynamic details from the input…
SemanticSplat: Feed-Forward 3D Scene Understanding with Language-Aware Gaussian Fields
Qijing Li, Jingxiang Sun, Liang An +3
Holistic 3D scene understanding, which jointly models geometry, appearance, and semantics, is crucial for applications like augmented reality and robotic interaction. Existing feed…
GAF: Gaussian Action Field as a 4D Representation for Dynamic World Modeling in Robotic Manipulation
Ying Chai, Litao Deng, Ruizhi Shao +6
Accurate scene perception is critical for vision-based robotic manipulation. Existing approaches typically follow either a Vision-to-Action (V-A) paradigm, predicting actions direc…
MetricHMSR:Metric Human Mesh and Scene Recovery from Monocular Images
Chentao Song, He Zhang, Haolei Yuan +4
We introduce MetricHMSR, a novel framework for recovering metric human meshes and 3D scenes from a single monocular image. Existing methods struggle to recover metric scale due to…
ManiVideo: Generating Hand-Object Manipulation Video with Dexterous and Generalizable Grasping
Youxin Pang, Ruizhi Shao, Jiajun Zhang +5
In this paper, we introduce ManiVideo, a novel method for generating consistent and temporally coherent bimanual hand-object manipulation videos from given motion sequences of hand…
Stereo-Talker: Audio-driven 3D Human Synthesis with Prior-Guided Mixture-of-Experts
Xiang Deng, Youxin Pang, Xiaochen Zhao +6
This paper introduces Stereo-Talker, a novel one-shot audio-driven human video synthesis system that generates 3D talking videos with precise lip synchronization, expressive body g…
Lodge++: High-quality and Long Dance Generation with Vivid Choreography Patterns
Ronghui Li, Hongwen Zhang, Yachao Zhang +6
We propose Lodge++, a choreography framework to generate high-quality, ultra-long, and vivid dances given the music and desired genre. To handle the challenges in computational eff…
ManiDext: Hand-Object Manipulation Synthesis via Continuous Correspondence Embeddings and Residual-Guided Diffusion
Jiajun Zhang, Yuxiang Zhang, Liang An +4
Dynamic and dexterous manipulation of objects presents a complex challenge, requiring the synchronization of hand motions with the trajectories of objects to achieve seamless and p…
HHMR: Holistic Hand Mesh Recovery by Enhancing the Multimodal Controllability of Graph Diffusion Models
Mengcheng Li, Hongwen Zhang, Yuxiang Zhang +3
Recent years have witnessed a trend of the deep integration of the generation and reconstruction paradigms. In this paper, we extend the ability of controllable generative models f…
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…
OmniHands: Towards Robust 4D Hand Mesh Recovery via A Versatile Transformer
Dixuan Lin, Yuxiang Zhang, Mengcheng Li +5
In this paper, we introduce OmniHands, a universal approach to recovering interactive hand meshes and their relative movement from monocular or multi-view inputs. Our approach addr…
Lodge: A Coarse to Fine Diffusion Network for Long Dance Generation Guided by the Characteristic Dance Primitives
Ronghui Li, YuXiang Zhang, Yachao Zhang +5
We propose Lodge, a network capable of generating extremely long dance sequences conditioned on given music. We design Lodge as a two-stage coarse to fine diffusion architecture, a…
STAF: 3D Human Mesh Recovery from Video with Spatio-Temporal Alignment Fusion
Wei Yao, Hongwen Zhang, Yunlian Sun +1
The recovery of 3D human mesh from monocular images has significantly been developed in recent years. However, existing models usually ignore spatial and temporal information, whic…
Ins-HOI: Instance Aware Human-Object Interactions Recovery
Jiajun Zhang, Yuxiang Zhang, Hongwen Zhang +5
Accurately modeling detailed interactions between human/hand and object is an appealing yet challenging task. Current multi-view capture systems are only capable of reconstructing…
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…
FG-MDM: Towards Zero-Shot Human Motion Generation via ChatGPT-Refined Descriptions
Xu Shi, Wei Yao, Chuanchen Luo +3
Recently, significant progress has been made in text-based motion generation, enabling the generation of diverse and high-quality human motions that conform to textual descriptions…
GaussianAvatar: Towards Realistic Human Avatar Modeling from a Single Video via Animatable 3D Gaussians
Liangxiao Hu, Hongwen Zhang, Yuxiang Zhang +4
We present GaussianAvatar, an efficient approach to creating realistic human avatars with dynamic 3D appearances from a single video. We start by introducing animatable 3D Gaussian…
HumanNorm: Learning Normal Diffusion Model for High-quality and Realistic 3D Human Generation
Xin Huang, Ruizhi Shao, Qi Zhang +4
Recent text-to-3D methods employing diffusion models have made significant advancements in 3D human generation. However, these approaches face challenges due to the limitations of…
W-HMR: Monocular Human Mesh Recovery in World Space with Weak-Supervised Calibration
Wei Yao, Hongwen Zhang, Yunlian Sun +2
Previous methods for 3D human motion recovery from monocular images often fall short due to reliance on camera coordinates, leading to inaccuracies in real-world applications. The…
HAvatar: High-fidelity Head Avatar via Facial Model Conditioned Neural Radiance Field
Xiaochen Zhao, Lizhen Wang, Jingxiang Sun +3
The problem of modeling an animatable 3D human head avatar under light-weight setups is of significant importance but has not been well solved. Existing 3D representations either p…
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…
CaPhy: Capturing Physical Properties for Animatable Human Avatars
Zhaoqi Su, Liangxiao Hu, Siyou Lin +4
We present CaPhy, a novel method for reconstructing animatable human avatars with realistic dynamic properties for clothing. Specifically, we aim for capturing the geometric and ph…