85 citations · 238 across the 41 of their papers we have counts for
44 papers
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…
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…
SAND: Spatially Adaptive Network Depth for Fast Sampling of Neural Implicit Surfaces
Chuanxiang Yang, Junhui Hou, Yuan Liu +5
Implicit neural representations are powerful for geometric modeling, but their practical use is often limited by the high computational cost of network evaluations. We observe that…
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…
BuildAnyPoint: 3D Building Structured Abstraction from Diverse Point Clouds
Tongyan Hua, Haoran Gong, Yuan Liu +3
We introduce BuildAnyPoint, a novel generative framework for structured 3D building reconstruction from point clouds with diverse distributions, such as those captured by airborne…
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…
Dynamic Gaussian Scene Reconstruction from Unsynchronized Videos
Zhixin Xu, Hengyu Zhou, Yuan Liu +4
Multi-view video reconstruction plays a vital role in computer vision, enabling applications in film production, virtual reality, and motion analysis. While recent advances such as…
T-MLP: Tailed Multi-Layer Perceptron for Level-of-Detail Signal Representation
Chuanxiang Yang, Yuanfeng Zhou, Guangshun Wei +4
Level-of-detail (LoD) representation is critical for efficiently modeling and transmitting various types of signals, such as images and 3D shapes. In this work, we propose a novel…
SPGen: Spherical Projection as Consistent and Flexible Representation for Single Image 3D Shape Generation
Jingdong Zhang, Weikai Chen, Yuan Liu +6
Existing single-view 3D generative models typically adopt multiview diffusion priors to reconstruct object surfaces, yet they remain prone to inter-view inconsistencies and are una…
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…
MEGS: Memory-Efficient Gaussian Splatting via Spherical Gaussians and Unified Pruning
Jiarui Chen, Yikeng Chen, Yingshuang Zou +5
3D Gaussian Splatting (3DGS) has emerged as a dominant novel-view synthesis technique, but its high memory consumption severely limits its applicability on edge devices. A growing…
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…
CrossGen: Learning and Generating Cross Fields for Quad Meshing
Qiujie Dong, Jiepeng Wang, Rui Xu +10
Cross fields play a critical role in various geometry processing tasks, especially for quad mesh generation. Existing methods for cross field generation often struggle to balance c…
3R-GS: Best Practice in Optimizing Camera Poses Along with 3DGS
Zhisheng Huang, Peng Wang, Jingdong Zhang +3
3D Gaussian Splatting (3DGS) has revolutionized neural rendering with its efficiency and quality, but like many novel view synthesis methods, it heavily depends on accurate camera…
MMGen: Unified Multi-modal Image Generation and Understanding in One Go
Jiepeng Wang, Zhaoqing Wang, Hao Pan +4
A unified diffusion framework for multi-modal generation and understanding has the transformative potential to achieve seamless and controllable image diffusion and other cross-mod…
CADDreamer: CAD Object Generation from Single-view Images
Yuan Li, Cheng Lin, Yuan Liu +6
Diffusion-based 3D generation has made remarkable progress in recent years. However, existing 3D generative models often produce overly dense and unstructured meshes, which stand i…
NeuralGS: Bridging Neural Fields and 3D Gaussian Splatting for Compact 3D Representations
Zhenyu Tang, Chaoran Feng, Xinhua Cheng +6
3D Gaussian Splatting (3DGS) achieves impressive quality and rendering speed, but with millions of 3D Gaussians and significant storage and transmission costs. In this paper, we ai…
GausSurf: Geometry-Guided 3D Gaussian Splatting for Surface Reconstruction
Jiepeng Wang, Yuan Liu, Peng Wang +5
3D Gaussian Splatting has achieved impressive performance in novel view synthesis with real-time rendering capabilities. However, reconstructing high-quality surfaces with fine det…
MotionWavelet: Human Motion Prediction via Wavelet Manifold Learning
Yuming Feng, Zhiyang Dou, Ling-Hao Chen +7
Modeling temporal characteristics and the non-stationary dynamics of body movement plays a significant role in predicting human future motions. However, it is challenging to captur…
SVGS: Enhancing Gaussian Splatting Using Primitives with Spatially Varying Colors
Rui Xu, Wenyue Chen, Jiepeng Wang +7
Gaussian Splatting demonstrates impressive results in multi-view reconstruction based on Gaussian explicit representations. However, the current Gaussian primitives only have a sin…
EasyHOI: Unleashing the Power of Large Models for Reconstructing Hand-Object Interactions in the Wild
Yumeng Liu, Xiaoxiao Long, Zemin Yang +5
Our work aims to reconstruct hand-object interactions from a single-view image, which is a fundamental but ill-posed task. Unlike methods that reconstruct from videos, multi-view i…
Monge-Ampere Regularization for Learning Arbitrary Shapes from Point Clouds
Chuanxiang Yang, Yuanfeng Zhou, Guangshun Wei +4
As commonly used implicit geometry representations, the signed distance function (SDF) is limited to modeling watertight shapes, while the unsigned distance function (UDF) is capab…
DICE: End-to-end Deformation Capture of Hand-Face Interactions from a Single Image
Qingxuan Wu, Zhiyang Dou, Sirui Xu +11
Reconstructing 3D hand-face interactions with deformations from a single image is a challenging yet crucial task with broad applications in AR, VR, and gaming. The challenges stem…
MoDGS: Dynamic Gaussian Splatting from Casually-captured Monocular Videos with Depth Priors
Qingming Liu, Yuan Liu, Jiepeng Wang +4
In this paper, we propose MoDGS, a new pipeline to render novel views of dy namic scenes from a casually captured monocular video. Previous monocular dynamic NeRF or Gaussian Splat…