2 citations · 2 across the 10 of their papers we have counts for
11 papers
NeuSpring: Neural Spring Fields for Reconstruction and Simulation of Deformable Objects from Videos
Qingshan Xu, Jiao Liu, Shangshu Yu +6
In this paper, we aim to create physical digital twins of deformable objects under interaction. Existing methods focus more on the physical learning of current state modeling, but…
DragNeXt: Rethinking Drag-Based Image Editing
Yuan Zhou, Junbao Zhou, Qingshan Xu +5
Drag-Based Image Editing (DBIE), which allows users to manipulate images by directly dragging objects within them, has recently attracted much attention from the community. However…
Personalize Your Gaussian: Consistent 3D Scene Personalization from a Single Image
Yuxuan Wang, Xuanyu Yi, Qingshan Xu +3
Personalizing 3D scenes from a single reference image enables intuitive user-guided editing, which requires achieving both multi-view consistency across perspectives and referentia…
Nautilus: Locality-aware Autoencoder for Scalable Mesh Generation
Yuxuan Wang, Xuanyu Yi, Haohan Weng +6
Triangle meshes are fundamental to 3D applications, enabling efficient modification and rasterization while maintaining compatibility with standard rendering pipelines. However, cu…
Pushing Rendering Boundaries: Hard Gaussian Splatting
Qingshan Xu, Jiequan Cui, Xuanyu Yi +4
3D Gaussian Splatting (3DGS) has demonstrated impressive Novel View Synthesis (NVS) results in a real-time rendering manner. During training, it relies heavily on the average magni…
Few-shot NeRF by Adaptive Rendering Loss Regularization
Qingshan Xu, Xuanyu Yi, Jianyao Xu +3
Novel view synthesis with sparse inputs poses great challenges to Neural Radiance Field (NeRF). Recent works demonstrate that the frequency regularization of Positional Encoding (P…
MVGamba: Unify 3D Content Generation as State Space Sequence Modeling
Xuanyu Yi, Zike Wu, Qiuhong Shen +6
Recent 3D large reconstruction models (LRMs) can generate high-quality 3D content in sub-seconds by integrating multi-view diffusion models with scalable multi-view reconstructors.…
Diffusion Time-step Curriculum for One Image to 3D Generation
Xuanyu Yi, Zike Wu, Qingshan Xu +3
Score distillation sampling~(SDS) has been widely adopted to overcome the absence of unseen views in reconstructing 3D objects from a \textbf{single} image. It leverages pre-traine…
Distributionally Generative Augmentation for Fair Facial Attribute Classification
Fengda Zhang, Qianpei He, Kun Kuang +5
Facial Attribute Classification (FAC) holds substantial promise in widespread applications. However, FAC models trained by traditional methodologies can be unfair by exhibiting acc…
Gamba: Marry Gaussian Splatting with Mamba for single view 3D reconstruction
Qiuhong Shen, Zike Wu, Xuanyu Yi +4
We tackle the challenge of efficiently reconstructing a 3D asset from a single image at millisecond speed. Existing methods for single-image 3D reconstruction are primarily based o…
View-Consistent 3D Editing with Gaussian Splatting
Yuxuan Wang, Xuanyu Yi, Zike Wu +3
The advent of 3D Gaussian Splatting (3DGS) has revolutionized 3D editing, offering efficient, high-fidelity rendering and enabling precise local manipulations. Currently, diffusion…