20 citations · 84 across the 28 of their papers we have counts for
30 papers
CGGT: Curve-Grounded Geometry Transformer for 3D Parametric Curve Reconstruction
Zhirui Gao, Renjiao Yi, Yunfan Ye +4
Recovering editable 3D parametric curves from 2D images is a fundamental challenge in computer graphics, bridging pixel-based perception and vector-based CAD modeling. Existing NeR…
HoloTetSphere: Unified TetSphere Mesh Reconstruction for Physical Simulations
YaQiao Dai, Renjiao Yi, Zhirui Gao +3
Standard pipelines for physics-ready 3D reconstruction rely on a decoupled two-stage paradigm: extracting surface geometry followed by an error-prone tetrahedralization process. Wh…
DynaMOMA: Instantaneous Prediction of Grasp Poses for Mobile Manipulation of Dynamic Objects
Zhinan Yu, Junyan Xu, Jiazhao Zhang +9
Mobile manipulation is a fundamental robotics task and has advanced rapidly in recent years, enabling robots to navigate, reach, and interact with objects in complex environments.…
PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation
Yuhang Huang, Xuan Lv, Junyan Xu +25
World foundation models (WFMs) are powerful simulators, yet they predominantly operate in a single-view setting and lack the multi-view 3D consistency required for robotic manipula…
CycleDiff: Cycle Diffusion Models for Unpaired Image-to-image Translation
Shilong Zou, Yuhang Huang, Renjiao Yi +2
We introduce a diffusion-based cross-domain image translator in the absence of paired training data. Unlike GAN-based methods, our approach integrates diffusion models to learn the…
Curve-Aware Gaussian Splatting for 3D Parametric Curve Reconstruction
Zhirui Gao, Renjiao Yi, Yaqiao Dai +4
This paper presents an end-to-end framework for reconstructing 3D parametric curves directly from multi-view edge maps. Contrasting with existing two-stage methods that follow a se…
RemixFusion: Residual-based Mixed Representation for Large-scale Online RGB-D Reconstruction
Yuqing Lan, Chenyang Zhu, Shuaifeng Zhi +5
The introduction of the neural implicit representation has notably propelled the advancement of online dense reconstruction techniques. Compared to traditional explicit representat…
Angio-Diff: Learning a Self-Supervised Adversarial Diffusion Model for Angiographic Geometry Generation
Zhifeng Wang, Renjiao Yi, Xin Wen +3
Vascular diseases pose a significant threat to human health, with X-ray angiography established as the gold standard for diagnosis, allowing for detailed observation of blood vesse…
BoxFusion: Reconstruction-Free Open-Vocabulary 3D Object Detection via Real-Time Multi-View Box Fusion
Yuqing Lan, Chenyang Zhu, Zhirui Gao +5
Open-vocabulary 3D object detection has gained significant interest due to its critical applications in autonomous driving and embodied AI. Existing detection methods, whether offl…
VasTSD: Learning 3D Vascular Tree-state Space Diffusion Model for Angiography Synthesis
Zhifeng Wang, Renjiao Yi, Xin Wen +2
Angiography imaging is a medical imaging technique that enhances the visibility of blood vessels within the body by using contrast agents. Angiographic images can effectively assis…
CAD-NeRF: Learning NeRFs from Uncalibrated Few-view Images by CAD Model Retrieval
Xin Wen, Xuening Zhu, Renjiao Yi +3
Reconstructing from multi-view images is a longstanding problem in 3D vision, where neural radiance fields (NeRFs) have shown great potential and get realistic rendered images of n…
Generic Objects as Pose Probes for Few-shot View Synthesis
Zhirui Gao, Renjiao Yi, Chenyang Zhu +3
Radiance fields including NeRFs and 3D Gaussians demonstrate great potential in high-fidelity rendering and scene reconstruction, while they require a substantial number of posed i…
Self-supervised Learning of Hybrid Part-aware 3D Representations of 2D Gaussians and Superquadrics
Zhirui Gao, Renjiao Yi, Yuhang Huang +3
Low-level 3D representations, such as point clouds, meshes, NeRFs and 3D Gaussians, are commonly used for modeling 3D objects and scenes. However, cognitive studies indicate that h…
Relighting Scenes with Object Insertions in Neural Radiance Fields
Xuening Zhu, Renjiao Yi, Xin Wen +2
The insertion of objects into a scene and relighting are commonly utilized applications in augmented reality (AR). Previous methods focused on inserting virtual objects using CAD m…
DISCO: Efficient Diffusion Solver for Large-Scale Combinatorial Optimization Problems
Hang Zhao, Kexiong Yu, Yuhang Huang +3
Combinatorial Optimization (CO) problems are fundamentally important in numerous real-world applications across diverse industries, characterized by entailing enormous solution spa…
F2M-Reg: Unsupervised RGB-D Point Cloud Registration with Frame-to-Model Optimization
Zhinan Yu, Zheng Qin, Yijie Tang +4
This work studies the problem of unsupervised RGB-D point cloud registration, which aims at training a robust registration model without ground-truth pose supervision. Existing met…
DiffusionEdge: Diffusion Probabilistic Model for Crisp Edge Detection
Yunfan Ye, Kai Xu, Yuhang Huang +2
Limited by the encoder-decoder architecture, learning-based edge detectors usually have difficulty predicting edge maps that satisfy both correctness and crispness. With the recent…
2D3D-MATR: 2D-3D Matching Transformer for Detection-free Registration between Images and Point Clouds
Minhao Li, Zheng Qin, Zhirui Gao +4
The commonly adopted detect-then-match approach to registration finds difficulties in the cross-modality cases due to the incompatible keypoint detection and inconsistent feature d…
Delving into Crispness: Guided Label Refinement for Crisp Edge Detection
Yunfan Ye, Renjiao Yi, Zhirui Gao +2
Learning-based edge detection usually suffers from predicting thick edges. Through extensive quantitative study with a new edge crispness measure, we find that noisy human-labeled…
Tensorformer: Normalized Matrix Attention Transformer for High-quality Point Cloud Reconstruction
Hui Tian, Zheng Qin, Renjiao Yi +2
Surface reconstruction from raw point clouds has been studied for decades in the computer graphics community, which is highly demanded by modeling and rendering applications nowada…
Weakly-supervised Single-view Image Relighting
Renjiao Yi, Chenyang Zhu, Kai Xu
We present a learning-based approach to relight a single image of Lambertian and low-frequency specular objects. Our method enables inserting objects from photographs into new scen…
NEF: Neural Edge Fields for 3D Parametric Curve Reconstruction from Multi-view Images
Yunfan Ye, Renjiao Yi, Zhirui Gao +3
We study the problem of reconstructing 3D feature curves of an object from a set of calibrated multi-view images. To do so, we learn a neural implicit field representing the densit…
Learning Accurate Template Matching with Differentiable Coarse-to-Fine Correspondence Refinement
Zhirui Gao, Renjiao Yi, Zheng Qin +3
Template matching is a fundamental task in computer vision and has been studied for decades. It plays an essential role in manufacturing industry for estimating the poses of differ…
Multi-resolution Monocular Depth Map Fusion by Self-supervised Gradient-based Composition
Yaqiao Dai, Renjiao Yi, Chenyang Zhu +2
Monocular depth estimation is a challenging problem on which deep neural networks have demonstrated great potential. However, depth maps predicted by existing deep models usually l…