activity
20182026
most citedROSEFusion: Random Optimization for Online Dense Reconstruction under Fast Camera Motion

217 citations · 307 across the 36 of their papers we have counts for

collaborators

37 papers

cs.GR2026

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…

cs.AI2026

Learning Flexible Job Shop Scheduling under Limited Buffers and Material Kitting Constraints

Shishun Zhang, Juzhan Xu, Yidan Fan +4

The Flexible Job Shop Scheduling Problem (FJSP) originates from real production lines, while some practical constraints are often ignored or idealized in current FJSP studies, amon…

cs.RO2025

RoboBPP: Benchmarking Robotic Online Bin Packing with Physics-based Simulation

Zhoufeng Wang, Hang Zhao, Juzhan Xu +8

Physical feasibility in 3D bin packing is a key requirement in modern industrial logistics and robotic automation. With the growing adoption of industrial automation, online bin pa…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

eess.IV2025

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…

cs.CV2025

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…

cs.RO2025

Deliberate Planning of 3D Bin Packing on Packing Configuration Trees

Hang Zhao, Juzhan Xu, Kexiong Yu +4

Online 3D Bin Packing Problem (3D-BPP) has widespread applications in industrial automation. Existing methods usually solve the problem with limited resolution of spatial discretiz…

cs.CV2025

OnlineAnySeg: Online Zero-Shot 3D Segmentation by Visual Foundation Model Guided 2D Mask Merging

Yijie Tang, Jiazhao Zhang, Yuqing Lan +4

Online zero-shot 3D instance segmentation of a progressively reconstructed scene is both a critical and challenging task for embodied applications. With the success of visual found…

cs.CV2025

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…

cs.CV2024★ 5 cited

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…

cs.RO2024

LLM-enhanced Scene Graph Learning for Household Rearrangement

Wenhao Li, Zhiyuan Yu, Qijin She +5

The household rearrangement task involves spotting misplaced objects in a scene and accommodate them with proper places. It depends both on common-sense knowledge on the objective…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 1 cited

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…

cs.CV2024★ 1 cited

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…

cs.AI2024★ 3 cited

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…

cs.CV2024

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…

cs.RO2024

Learning Dual-arm Object Rearrangement for Cartesian Robots

Shishun Zhang, Qijin She, Wenhao Li +4

This work focuses on the dual-arm object rearrangement problem abstracted from a realistic industrial scenario of Cartesian robots. The goal of this problem is to transfer all the…

cs.CV2023★ 1 cited

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…

cs.CV2023★ 1 cited

SuperUDF: Self-supervised UDF Estimation for Surface Reconstruction

Hui Tian, Chenyang Zhu, Yifei Shi +1

Learning-based surface reconstruction based on unsigned distance functions (UDF) has many advantages such as handling open surfaces. We propose SuperUDF, a self-supervised UDF lear…

cs.GR2023

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…

cs.CV2023

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…

cs.CV2023★ 1 cited

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…