57 citations · 102 across the 31 of their papers we have counts for
33 papers
PartLLM: A Unified Multimodal Foundation for 3D Part Segmentation
Zhe Zhu, Yiheng Zhang, Peng Li +9
Part segmentation is a fundamental problem in computer graphics and 3D vision. Recent works have expanded 3D part segmentation beyond fixed taxonomies, but existing approaches typi…
BladeYOLO: Wind Turbine Blade Defect Detection with Limited Annotations and Weak-Saliency Awareness
Yabin Xu, Fangtao Zhang, Fan Wang +5
Wind turbine blade defect detection remains highly challenging in real-world inspection scenarios due to limited on-site data and the subtle visual characteristics of defects. In p…
Efficient RWKV-based Representation Learning for 3D Point Clouds
Yun Liu, Xuefeng Yan, Liangliang Nan +5
The recent receptance weighted key value (RWKV) model combines RNN-style recurrence, offering a linear-complexity alternative to Transformers' quadratic self-attention for modeling…
ArtiLatent: Realistic Articulated 3D Object Generation via Structured Latents
Honghua Chen, Yushi Lan, Yongwei Chen +1
We propose ArtiLatent, a generative framework that synthesizes human-made 3D objects with fine-grained geometry, accurate articulation, and realistic appearance. Our approach joint…
PartSAM: A Scalable Promptable Part Segmentation Model Trained on Native 3D Data
Zhe Zhu, Le Wan, Rui Xu +6
Segmenting 3D objects into parts is a long-standing challenge in computer vision. To overcome taxonomy constraints and generalize to unseen 3D objects, recent works turn to open-wo…
STream3R: Scalable Sequential 3D Reconstruction with Causal Transformer
Yushi Lan, Yihang Luo, Fangzhou Hong +7
We present STream3R, a novel approach to 3D reconstruction that reformulates pointmap prediction as a decoder-only Transformer problem. Existing state-of-the-art methods for multi-…
CoreEditor: Correspondence-constrained Diffusion for Consistent 3D Editing
Zhe Zhu, Honghua Chen, Peng Li +1
Text-driven 3D editing seeks to modify 3D scenes according to textual descriptions, and most existing approaches tackle this by adapting pre-trained 2D image editors to multi-view…
RARE: Refine Any Registration of Pairwise Point Clouds via Zero-Shot Learning
Chengyu Zheng, Jin Huang, Honghua Chen +1
Recent research leveraging large-scale pretrained diffusion models has demonstrated the potential of using diffusion features to establish semantic correspondences in images. Inspi…
I Speak and You Find: Robust 3D Visual Grounding with Noisy and Ambiguous Speech Inputs
Yu Qi, Lipeng Gu, Honghua Chen +2
Existing 3D visual grounding methods rely on precise text prompts to locate objects within 3D scenes. Speech, as a natural and intuitive modality, offers a promising alternative. R…
Unified Representation Space for 3D Visual Grounding
Yinuo Zheng, Lipeng Gu, Honghua Chen +2
3D visual grounding (3DVG) is a critical task in scene understanding that aims to identify objects in 3D scenes based on text descriptions. However, existing methods rely on separa…
Hierarchical Error Assessment of CAD Models for Aircraft Manufacturing-and-Measurement
Jin Huang, Honghua Chen, Mingqiang Wei
The most essential feature of aviation equipment is high quality, including high performance, high stability and high reliability. In this paper, we propose a novel hierarchical er…
BridgeShape: Latent Diffusion Schrödinger Bridge for 3D Shape Completion
Dequan Kong, Honghua Chen, Zhe Zhu +1
Existing diffusion-based 3D shape completion methods typically use a conditional paradigm, injecting incomplete shape information into the denoising network via deep feature intera…
PointSFDA: Source-free Domain Adaptation for Point Cloud Completion
Xing He, Zhe Zhu, Liangliang Nan +3
Conventional methods for point cloud completion, typically trained on synthetic datasets, face significant challenges when applied to out-of-distribution real-world scans. In this…
STAR-Edge: Structure-aware Local Spherical Curve Representation for Thin-walled Edge Extraction from Unstructured Point Clouds
Zikuan Li, Honghua Chen, Yuecheng Wang +3
Extracting geometric edges from unstructured point clouds remains a significant challenge, particularly in thin-walled structures that are commonly found in everyday objects. Tradi…
PointSea: Point Cloud Completion via Self-structure Augmentation
Zhe Zhu, Honghua Chen, Xing He +1
Point cloud completion is a fundamental yet not well-solved problem in 3D vision. Current approaches often rely on 3D coordinate information and/or additional data (e.g., images an…
Textured 3D Regenerative Morphing with 3D Diffusion Prior
Songlin Yang, Yushi Lan, Honghua Chen +1
Textured 3D morphing creates smooth and plausible interpolation sequences between two 3D objects, focusing on transitions in both shape and texture. This is important for creative…
CrossTracker: Robust Multi-modal 3D Multi-Object Tracking via Cross Correction
Lipeng Gu, Xuefeng Yan, Weiming Wang +4
The fusion of camera- and LiDAR-based detections offers a promising solution to mitigate tracking failures in 3D multi-object tracking (MOT). However, existing methods predominantl…
PointCG: Self-supervised Point Cloud Learning via Joint Completion and Generation
Yun Liu, Peng Li, Xuefeng Yan +6
The core of self-supervised point cloud learning lies in setting up appropriate pretext tasks, to construct a pre-training framework that enables the encoder to perceive 3D objects…
MvDrag3D: Drag-based Creative 3D Editing via Multi-view Generation-Reconstruction Priors
Honghua Chen, Yushi Lan, Yongwei Chen +2
Drag-based editing has become popular in 2D content creation, driven by the capabilities of image generative models. However, extending this technique to 3D remains a challenge. Ex…
MVIP-NeRF: Multi-view 3D Inpainting on NeRF Scenes via Diffusion Prior
Honghua Chen, Chen Change Loy, Xingang Pan
Despite the emergence of successful NeRF inpainting methods built upon explicit RGB and depth 2D inpainting supervisions, these methods are inherently constrained by the capabiliti…
PointeNet: A Lightweight Framework for Effective and Efficient Point Cloud Analysis
Lipeng Gu, Xuefeng Yan, Liangliang Nan +4
Current methodologies in point cloud analysis predominantly explore 3D geometries, often achieved through the introduction of intricate learnable geometric extractors in the encode…
SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator
Zhe Zhu, Honghua Chen, Xing He +3
In this paper, we propose a novel network, SVDFormer, to tackle two specific challenges in point cloud completion: understanding faithful global shapes from incomplete point clouds…
LBF:Learnable Bilateral Filter For Point Cloud Denoising
Huajian Si, Zeyong Wei, Zhe Zhu +4
Bilateral filter (BF) is a fast, lightweight and effective tool for image denoising and well extended to point cloud denoising. However, it often involves continual yet manual para…
GeoGCN: Geometric Dual-domain Graph Convolution Network for Point Cloud Denoising
Zhaowei Chen, Peng Li, Zeyong Wei +4
We propose GeoGCN, a novel geometric dual-domain graph convolution network for point cloud denoising (PCD). Beyond the traditional wisdom of PCD, to fully exploit the geometric inf…