22 citations · 45 across the 17 of their papers we have counts for
17 papers
CustomTex: High-fidelity Indoor Scene Texturing via Multi-Reference Customization
Weilin Chen, Jiahao Rao, Wenhao Wang +3
The creation of high-fidelity, customizable 3D indoor scene textures remains a significant challenge. While text-driven methods offer flexibility, they lack the precision for fine-…
FlashWorld: High-quality 3D Scene Generation within Seconds
Xinyang Li, Tengfei Wang, Zixiao Gu +3
We propose FlashWorld, a generative model that produces 3D scenes from a single image or text prompt in seconds, 10~100 faster than previous works while possessing superior…
XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
Dian Chen, Yansong Qu, Xinyang Li +2
Current auto-regressive models can generate high-quality, topologically precise meshes; however, they necessitate thousands-or even tens of thousands-of next-token predictions duri…
DeOcc-1-to-3: 3D De-Occlusion from a Single Image via Self-Supervised Multi-View Diffusion
Yansong Qu, Shaohui Dai, Xinyang Li +4
Reconstructing 3D objects from a single image remains challenging, especially under real-world occlusions. While recent diffusion-based view synthesis models can generate consisten…
SynergyAmodal: Deocclude Anything with Text Control
Xinyang Li, Chengjie Yi, Jiawei Lai +4
Image deocclusion (or amodal completion) aims to recover the invisible regions (\ie, shape and appearance) of occluded instances in images. Despite recent advances, the scarcity of…
Training-Free Hierarchical Scene Understanding for Gaussian Splatting with Superpoint Graphs
Shaohui Dai, Yansong Qu, Zheyan Li +3
Bridging natural language and 3D geometry is a crucial step toward flexible, language-driven scene understanding. While recent advances in 3D Gaussian Splatting (3DGS) have enabled…
AnomalyPainter: Vision-Language-Diffusion Synergy for Zero-Shot Realistic and Diverse Industrial Anomaly Synthesis
Zhangyu Lai, Yilin Lu, Xinyang Li +5
While existing anomaly synthesis methods have made remarkable progress, achieving both realism and diversity in synthesis remains a major obstacle. To address this, we propose Anom…
Evolving High-Quality Rendering and Reconstruction in a Unified Framework with Contribution-Adaptive Regularization
You Shen, Zhipeng Zhang, Xinyang Li +4
Representing 3D scenes from multiview images is a core challenge in computer vision and graphics, which requires both precise rendering and accurate reconstruction. Recently, 3D Ga…
Prometheus: 3D-Aware Latent Diffusion Models for Feed-Forward Text-to-3D Scene Generation
Yuanbo Yang, Jiahao Shao, Xinyang Li +3
In this work, we introduce Prometheus, a 3D-aware latent diffusion model for text-to-3D generation at both object and scene levels in seconds. We formulate 3D scene generation as m…
Drag Your Gaussian: Effective Drag-Based Editing with Score Distillation for 3D Gaussian Splatting
Yansong Qu, Dian Chen, Xinyang Li +4
Recent advancements in 3D scene editing have been propelled by the rapid development of generative models. Existing methods typically utilize generative models to perform text-guid…
Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text
Xinyang Li, Zhangyu Lai, Linning Xu +5
Recent advancements in 3D generation have leveraged synthetic datasets with ground truth 3D assets and predefined cameras. However, the potential of adopting real-world datasets, w…
Dual3D: Efficient and Consistent Text-to-3D Generation with Dual-mode Multi-view Latent Diffusion
Xinyang Li, Zhangyu Lai, Linning Xu +5
We present Dual3D, a novel text-to-3D generation framework that generates high-quality 3D assets from texts in only minute.The key component is a dual-mode multi-view latent di…
GOI: Find 3D Gaussians of Interest with an Optimizable Open-vocabulary Semantic-space Hyperplane
Yansong Qu, Shaohui Dai, Xinyang Li +4
3D open-vocabulary scene understanding, crucial for advancing augmented reality and robotic applications, involves interpreting and locating specific regions within a 3D space as d…
NeRF-DetS: Enhanced Adaptive Spatial-wise Sampling and View-wise Fusion Strategies for NeRF-based Indoor Multi-view 3D Object Detection
Chi Huang, Xinyang Li, Yansong Qu +4
In indoor scenes, the diverse distribution of object locations and scales makes the visual 3D perception task a big challenge. Previous works (e.g, NeRF-Det) have demonstrated that…
StreetSurf: Extending Multi-view Implicit Surface Reconstruction to Street Views
Jianfei Guo, Nianchen Deng, Xinyang Li +6
We present a novel multi-view implicit surface reconstruction technique, termed StreetSurf, that is readily applicable to street view images in widely-used autonomous driving datas…
Image-to-image Translation via Hierarchical Style Disentanglement
Xinyang Li, Shengchuan Zhang, Jie Hu +6
Recently, image-to-image translation has made significant progress in achieving both multi-label (\ie, translation conditioned on different labels) and multi-style (\ie, generation…
Attribute Guided Unpaired Image-to-Image Translation with Semi-supervised Learning
Xinyang Li, Jie Hu, Shengchuan Zhang +4
Unpaired Image-to-Image Translation (UIT) focuses on translating images among different domains by using unpaired data, which has received increasing research focus due to its prac…