activity
20192026
most citedCASE: Learning Conditional Adversarial Skill Embeddings for Physics-based Characters

39 citations · 96 across the 41 of their papers we have counts for

collaborators

48 papers

cs.CV2026

MOMO: Human Motion from Moving Sounds

Deli Cai, Shuyang Xu, Zhiyang Dou +4

Human responses to sound depend not only on its semantic content, but also on the evolving spatial relationship between source and listener, conveyed through spatial audio and its…

cs.CV2026

TKCAM: Text and Keyframe to Camera Trajectory Generation

Haozhe Yang, Zhiyang Dou, Zekai Gu +4

Generating high-quality and controllable camera motion is essential for AI-assisted cinematography, video synthesis, and 3D scene understanding. We introduce TKCAM, a Text- and Key…

cs.CV2026

TrackFish3D: Self-Supervised 3D Tracking of Schooling Fish from Multi-view Videos

Patt Phurtivilai, Zhiyang Dou, Yifan Wu +5

Quantifying collective fish behavior requires accurate trajectories, yet multi-view 3D tracking remains challenging due to frequent occlusions, visually similar individuals, and th…

cs.CV2026

PartLLM: A Unified Multimodal Foundation for 3D Part Segmentation

Zhe Zhu, Yiheng Zhang, Peng Li +9

Part segmentation is a fundamental problem in computer graphics and 3D vision. Recent works have expanded 3D part segmentation beyond fixed taxonomies, but existing approaches typi…

cs.GR2026

MoSAT: Human Motion Generation from Spatial Audio and Textual Description

Shuyang Xu, Zhiyang Dou, Yiduo Hao +8

Human motion is shaped by both external acoustic events and behavioral intent: spatial audio conveys environmental cues that elicit or guide a response, while text specifies the de…

cs.CV2026

Ms. Forcing: Efficient Streaming Video Generation with Multi-Scale Patchification and Attention

Zekun Li, Xiaoyan Cong, Hongyu Li +5

Streaming video diffusion models have made substantial progress toward interactive and dynamic world simulation, but the nested autoregressive and denoising loops of conventional n…

cs.RO2026

RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies

Tianxing Chen, Yue Chen, Zixuan Li +41

Generalist robot manipulation policies have advanced rapidly, yet existing benchmarks remain limited in systematically evaluating their capabilities. Many rely on simple, short-hor…

cs.GR2026

QuadLink: Autoregressive Quad-Dominant Mesh Generation via Point-Relation Learning

Yiheng Zhang, Zhe Zhu, Tingrui Shen +11

The generation of production-ready quad-dominant meshes is a cornerstone of modern 3D content creation. Generating anisotropic quad-dominant meshes from point clouds is challenging…

cs.CV2026

GaussiAnimate: Rig Animatable Categories with Level of Dynamics

Jiaxin Wang, Dongxin Lyu, Zeyu Cai +4

We propose Skelebones, a Scaffold-Skin Rigging System built on three steps: (1) Bones compress temporally consistent Gaussian or mesh sequences into free-form bones with smooth ski…

cs.CV2026

UNIC: Neural Garment Deformation Field for Real-time Clothed Character Animation

Chengfeng Zhao, Junbo Qi, Yulou Liu +6

Simulating physically realistic garment deformations is an essential task for virtual immersive experience, which is often achieved by physics simulation methods. However, these me…

cs.CV2026

UMO: Unified In-Context Learning Unlocks Motion Foundation Model Priors

Xiaoyan Cong, Zekun Li, Zhiyang Dou +9

Large-scale foundation models (LFMs) have recently made impressive progress in text-to-motion generation by learning strong generative priors from massive 3D human motion datasets…

cs.LG2026★ 1 cited

GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training

Haixu Wu, Minghao Guo, Zongyi Li +4

Neural simulators promise efficient surrogates for physics simulation, but scaling them is bottlenecked by the prohibitive cost of generating high-fidelity training data. Pre-train…

cs.CV2026

EgoReAct: Egocentric Video-Driven 3D Human Reaction Generation

Libo Zhang, Zekun Li, Tianyu Li +10

Humans exhibit adaptive, context-sensitive responses to egocentric visual input. However, faithfully modeling such reactions from egocentric video remains challenging due to the du…

cs.CV2026

CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos

Chengfeng Zhao, Jiazhi Shu, Yubo Zhao +7

In this paper, we find that the generation of 3D human motions and 2D human videos is intrinsically coupled. 3D motions provide the structural prior for plausibility and consistenc…

cs.CV2025

TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels

Jiahao Lu, Weitao Xiong, Jiacheng Deng +6

Monocular 3D tracking aims to capture the long-term motion of pixels in 3D space from a single monocular video and has witnessed rapid progress in recent years. However, we argue t…

cs.CV2025★ 2 cited

Wonder3D++: Cross-domain Diffusion for High-fidelity 3D Generation from a Single Image

Yuxiao Yang, Xiao-Xiao Long, Zhiyang Dou +7

In this work, we introduce \textbf{Wonder3D++}, a novel method for efficiently generating high-fidelity textured meshes from single-view images. Recent methods based on Score Disti…

cs.CV2025

SyncHuman: Synchronizing 2D and 3D Generative Models for Single-view Human Reconstruction

Wenyue Chen, Peng Li, Wangguandong Zheng +6

Photorealistic 3D full-body human reconstruction from a single image is a critical yet challenging task for applications in films and video games due to inherent ambiguities and se…

cs.CV2025

Text2Interact: High-Fidelity and Diverse Text-to-Two-Person Interaction Generation

Qingxuan Wu, Zhiyang Dou, Chuan Guo +5

Modeling human-human interactions from text remains challenging because it requires not only realistic individual dynamics but also precise, text-consistent spatiotemporal coupling…

cs.CV2025

PartSAM: A Scalable Promptable Part Segmentation Model Trained on Native 3D Data

Zhe Zhu, Le Wan, Rui Xu +6

Segmenting 3D objects into parts is a long-standing challenge in computer vision. To overcome taxonomy constraints and generalize to unseen 3D objects, recent works turn to open-wo…

cs.CV2025

PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video Generation

Chen Wang, Chuhao Chen, Yiming Huang +4

Existing video generation models excel at producing photo-realistic videos from text or images, but often lack physical plausibility and 3D controllability. To overcome these limit…

cs.GR2025

MeshMosaic: Scaling Artist Mesh Generation via Local-to-Global Assembly

Rui Xu, Tianyang Xue, Qiujie Dong +9

Scaling artist-designed meshes to high triangle numbers remains challenging for autoregressive generative models. Existing transformer-based methods suffer from long-sequence bottl…

cs.CV2025

Motion2Motion: Cross-topology Motion Transfer with Sparse Correspondence

Ling-Hao Chen, Yuhong Zhang, Zixin Yin +5

This work studies the challenge of transfer animations between characters whose skeletal topologies differ substantially. While many techniques have advanced retargeting techniques…

cs.CV2025

PDT: Point Distribution Transformation with Diffusion Models

Jionghao Wang, Cheng Lin, Yuan Liu +7

Point-based representations have consistently played a vital role in geometric data structures. Most point cloud learning and processing methods typically leverage the unordered an…

cs.GR2025

MOSPA: Human Motion Generation Driven by Spatial Audio

Shuyang Xu, Zhiyang Dou, Mingyi Shi +8

Enabling virtual humans to dynamically and realistically respond to diverse auditory stimuli remains a key challenge in character animation, demanding the integration of perceptual…