2 citations · 5 across the 16 of their papers we have counts for
18 papers
EviStress: Evidence Stress Learning for Generalizable Face Forgery Detection with Textual Explanations
Jiuyao Jing, Xuanyu Yi, Yu Zheng +1
The rapid spread of face forgeries on the Web challenges the credibility of visual content. In practical Web environments, manipulated media originate from evolving generation pipe…
Seed3D 2.0: Advancing High-Fidelity Simulation-Ready 3D Content Generation
Diandian Gu, Jing Lin, Gaohong Liu +25
We present Seed3D 2.0, an advanced 3D content generation system built on Seed3D 1.0, with substantial improvements across generation fidelity, simulation-ready capabilities, and ap…
TopoMesh: High-Fidelity Mesh Autoencoding via Topological Unification
Guan Luo, Xiu Li, Rui Chen +6
The dominant paradigm for high-fidelity 3D generation relies on a VAE-Diffusion pipeline, where the VAE's reconstruction capability sets a firm upper bound on generation quality. A…
Seed3D 1.0: From Images to High-Fidelity Simulation-Ready 3D Assets
Jiashi Feng, Xiu Li, Jing Lin +25
Developing embodied AI agents requires scalable training environments that balance content diversity with physics accuracy. World simulators provide such environments but face dist…
StreamSplat: Towards Online Dynamic 3D Reconstruction from Uncalibrated Video Streams
Zike Wu, Qi Yan, Xuanyu Yi +2
Real-time reconstruction of dynamic 3D scenes from uncalibrated video streams demands robust online methods that recover scene dynamics from sparse observations under strict latenc…
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…
Seeing World Dynamics in a Nutshell
Qiuhong Shen, Xuanyu Yi, Mingbao Lin +3
We consider the problem of efficiently representing casually captured monocular videos in a spatially- and temporally-coherent manner. While existing approaches predominantly rely…
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…
MMPKUBase: A Comprehensive and High-quality Chinese Multi-modal Knowledge Graph
Xuan Yi, Yanzeng Li, Lei Zou
Multi-modal knowledge graphs have emerged as a powerful approach for information representation, combining data from different modalities such as text, images, and videos. While se…
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…
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…
Consistent3D: Towards Consistent High-Fidelity Text-to-3D Generation with Deterministic Sampling Prior
Zike Wu, Pan Zhou, Xuanyu Yi +2
Score distillation sampling (SDS) and its variants have greatly boosted the development of text-to-3D generation, but are vulnerable to geometry collapse and poor textures yet. To…
Invariant Training 2D-3D Joint Hard Samples for Few-Shot Point Cloud Recognition
Xuanyu Yi, Jiajun Deng, Qianru Sun +3
We tackle the data scarcity challenge in few-shot point cloud recognition of 3D objects by using a joint prediction from a conventional 3D model and a well-trained 2D model. Surpri…
Identifying Hard Noise in Long-Tailed Sample Distribution
Xuanyu Yi, Kaihua Tang, Xian-Sheng Hua +2
Conventional de-noising methods rely on the assumption that all samples are independent and identically distributed, so the resultant classifier, though disturbed by noise, can sti…