110 citations · 354 across the 23 of their papers we have counts for
24 papers
Bridging Semantic and Kinematic Conditions with Diffusion-based Discrete Motion Tokenizer
Chenyang Gu, Mingyuan Zhang, Haozhe Xie +3
Prior motion generation largely follows two paradigms: continuous diffusion models that excel at kinematic control, and discrete token-based generators that are effective for seman…
InfiniteDance: Scalable 3D Dance Generation Towards in-the-wild Generalization
Ronghui Li, Zhongyuan Hu, Li Siyao +6
Although existing 3D dance generation methods perform well in controlled scenarios, they often struggle to generalize in the wild. When conditioned on unseen music, existing method…
SMPLest-X: Ultimate Scaling for Expressive Human Pose and Shape Estimation
Wanqi Yin, Zhongang Cai, Ruisi Wang +12
Expressive human pose and shape estimation (EHPS) unifies body, hands, and face motion capture with numerous applications. Despite encouraging progress, current state-of-the-art me…
RMD: A Simple Baseline for More General Human Motion Generation via Training-free Retrieval-Augmented Motion Diffuse
Zhouyingcheng Liao, Mingyuan Zhang, Wenjia Wang +2
While motion generation has made substantial progress, its practical application remains constrained by dataset diversity and scale, limiting its ability to handle out-of-distribut…
CrowdMoGen: Zero-Shot Text-Driven Collective Motion Generation
Yukang Cao, Xinying Guo, Mingyuan Zhang +3
While recent advances in text-to-motion generation have shown promising results, they typically assume all individuals are grouped as a single unit. Scaling these methods to handle…
Large Motion Model for Unified Multi-Modal Motion Generation
Mingyuan Zhang, Daisheng Jin, Chenyang Gu +8
Human motion generation, a cornerstone technique in animation and video production, has widespread applications in various tasks like text-to-motion and music-to-dance. Previous wo…
Multi-scale 2D Temporal Map Diffusion Models for Natural Language Video Localization
Chongzhi Zhang, Mingyuan Zhang, Zhiyang Teng +5
Natural Language Video Localization (NLVL), grounding phrases from natural language descriptions to corresponding video segments, is a complex yet critical task in video understand…
InsActor: Instruction-driven Physics-based Characters
Jiawei Ren, Mingyuan Zhang, Cunjun Yu +3
Generating animation of physics-based characters with intuitive control has long been a desirable task with numerous applications. However, generating physically simulated animatio…
FineMoGen: Fine-Grained Spatio-Temporal Motion Generation and Editing
Mingyuan Zhang, Huirong Li, Zhongang Cai +3
Text-driven motion generation has achieved substantial progress with the emergence of diffusion models. However, existing methods still struggle to generate complex motion sequence…
Digital Life Project: Autonomous 3D Characters with Social Intelligence
Zhongang Cai, Jianping Jiang, Zhongfei Qing +20
In this work, we present Digital Life Project, a framework utilizing language as the universal medium to build autonomous 3D characters, who are capable of engaging in social inter…
SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation
Zhongang Cai, Wanqi Yin, Ailing Zeng +10
Expressive human pose and shape estimation (EHPS) unifies body, hands, and face motion capture with numerous applications. Despite encouraging progress, current state-of-the-art me…
PointHPS: Cascaded 3D Human Pose and Shape Estimation from Point Clouds
Zhongang Cai, Liang Pan, Chen Wei +6
Human pose and shape estimation (HPS) has attracted increasing attention in recent years. While most existing studies focus on HPS from 2D images or videos with inherent depth ambi…
ReMoDiffuse: Retrieval-Augmented Motion Diffusion Model
Mingyuan Zhang, Xinying Guo, Liang Pan +5
3D human motion generation is crucial for creative industry. Recent advances rely on generative models with domain knowledge for text-driven motion generation, leading to substanti…
BiBench: Benchmarking and Analyzing Network Binarization
Haotong Qin, Mingyuan Zhang, Yifu Ding +5
Network binarization emerges as one of the most promising compression approaches offering extraordinary computation and memory savings by minimizing the bit-width. However, recent…
MotionDiffuse: Text-Driven Human Motion Generation with Diffusion Model
Mingyuan Zhang, Zhongang Cai, Liang Pan +4
Human motion modeling is important for many modern graphics applications, which typically require professional skills. In order to remove the skill barriers for laymen, recent moti…
AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars
Fangzhou Hong, Mingyuan Zhang, Liang Pan +3
3D avatar creation plays a crucial role in the digital age. However, the whole production process is prohibitively time-consuming and labor-intensive. To democratize this technolog…
HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling
Zhongang Cai, Daxuan Ren, Ailing Zeng +12
4D human sensing and modeling are fundamental tasks in vision and graphics with numerous applications. With the advances of new sensors and algorithms, there is an increasing deman…
BiBERT: Accurate Fully Binarized BERT
Haotong Qin, Yifu Ding, Mingyuan Zhang +5
The large pre-trained BERT has achieved remarkable performance on Natural Language Processing (NLP) tasks but is also computation and memory expensive. As one of the powerful compr…
Playing for 3D Human Recovery
Zhongang Cai, Mingyuan Zhang, Jiawei Ren +7
Image- and video-based 3D human recovery (i.e., pose and shape estimation) have achieved substantial progress. However, due to the prohibitive cost of motion capture, existing data…
CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing
Daxuan Ren, Jianmin Zheng, Jianfei Cai +8
Generating an interpretable and compact representation of 3D shapes from point clouds is an important and challenging problem. This paper presents CSG-Stump Net, an unsupervised en…
Delving Deep into the Generalization of Vision Transformers under Distribution Shifts
Chongzhi Zhang, Mingyuan Zhang, Shanghang Zhang +6
Vision Transformers (ViTs) have achieved impressive performance on various vision tasks, yet their generalization under distribution shifts (DS) is rarely understood. In this work,…
Towards Overcoming False Positives in Visual Relationship Detection
Daisheng Jin, Xiao Ma, Chongzhi Zhang +8
In this paper, we investigate the cause of the high false positive rate in Visual Relationship Detection (VRD). We observe that during training, the relationship proposal distribut…
BiPointNet: Binary Neural Network for Point Clouds
Haotong Qin, Zhongang Cai, Mingyuan Zhang +5
To alleviate the resource constraint for real-time point cloud applications that run on edge devices, in this paper we present BiPointNet, the first model binarization approach for…
Efficient Attention: Attention with Linear Complexities
Zhuoran Shen, Mingyuan Zhang, Haiyu Zhao +2
Dot-product attention has wide applications in computer vision and natural language processing. However, its memory and computational costs grow quadratically with the input size.…