3 citations · 5 across the 11 of their papers we have counts for
11 papers · 1 filter
InterDance:Reactive 3D Dance Generation with Realistic Duet Interactions
Ronghui Li, Youliang Zhang, Yachao Zhang +6
Humans perform a variety of interactive motions, among which duet dance is one of the most challenging interactions. However, in terms of human motion generative models, existing w…
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…
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…
TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understanding
Yun Liu, Haolin Yang, Xu Si +5
Humans commonly work with multiple objects in daily life and can intuitively transfer manipulation skills to novel objects by understanding object functional regularities. However,…
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…
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…
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…
ProxyCap: Real-time Monocular Full-body Capture in World Space via Human-Centric Proxy-to-Motion Learning
Yuxiang Zhang, Hongwen Zhang, Liangxiao Hu +4
Learning-based approaches to monocular motion capture have recently shown promising results by learning to regress in a data-driven manner. However, due to the challenges in data c…