39 citations · 96 across the 41 of their papers we have counts for
19 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Vid2Sim: Generalizable, Video-based Reconstruction of Appearance, Geometry and Physics for Mesh-free Simulation
Chuhao Chen, Zhiyang Dou, Chen Wang +5
Faithfully reconstructing textured shapes and physical properties from videos presents an intriguing yet challenging problem. Significant efforts have been dedicated to advancing s…
CoDA: Coordinated Diffusion Noise Optimization for Whole-Body Manipulation of Articulated Objects
Huaijin Pi, Zhi Cen, Zhiyang Dou +1
Synthesizing whole-body manipulation of articulated objects, including body motion, hand motion, and object motion, is a critical yet challenging task with broad applications in vi…
TokenHSI: Unified Synthesis of Physical Human-Scene Interactions through Task Tokenization
Liang Pan, Zeshi Yang, Zhiyang Dou +5
Synthesizing diverse and physically plausible Human-Scene Interactions (HSI) is pivotal for both computer animation and embodied AI. Despite encouraging progress, current methods m…
CBIL: Collective Behavior Imitation Learning for Fish from Real Videos
Yifan Wu, Zhiyang Dou, Yuko Ishiwaka +5
Reproducing realistic collective behaviors presents a captivating yet formidable challenge. Traditional rule-based methods rely on hand-crafted principles, limiting motion diversit…
ModSkill: Physical Character Skill Modularization
Yiming Huang, Zhiyang Dou, Lingjie Liu
Human motion is highly diverse and dynamic, posing challenges for imitation learning algorithms that aim to generalize motor skills for controlling simulated characters. Previous m…
MVTokenFlow: High-quality 4D Content Generation using Multiview Token Flow
Hanzhuo Huang, Yuan Liu, Ge Zheng +3
In this paper, we present MVTokenFlow for high-quality 4D content creation from monocular videos. Recent advancements in generative models such as video diffusion models and multiv…
WonderHuman: Hallucinating Unseen Parts in Dynamic 3D Human Reconstruction
Zilong Wang, Zhiyang Dou, Yuan Liu +7
In this paper, we present WonderHuman to reconstruct dynamic human avatars from a monocular video for high-fidelity novel view synthesis. Previous dynamic human avatar reconstructi…
Diffusion as Shader: 3D-aware Video Diffusion for Versatile Video Generation Control
Zekai Gu, Rui Yan, Jiahao Lu +9
Diffusion models have demonstrated impressive performance in generating high-quality videos from text prompts or images. However, precise control over the video generation process,…
ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking
Tingyang Zhang, Chen Wang, Zhiyang Dou +4
We propose ProTracker, a novel framework for accurate and robust long-term dense tracking of arbitrary points in videos. Previous methods relying on global cost volumes effectively…