2 citations · 3 across the 8 of their papers we have counts for
8 papers
ColorGS: High-fidelity Surgical Scene Reconstruction with Colored Gaussian Splatting
Qun Ji, Peng Li, Mingqiang Wei
High-fidelity reconstruction of deformable tissues from endoscopic videos remains challenging due to the limitations of existing methods in capturing subtle color variations and mo…
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…
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…
Efficient Deep Learning Board: Training Feedback Is Not All You Need
Lina Gong, Qi Gao, Peng Li +2
Current automatic deep learning (i.e., AutoDL) frameworks rely on training feedback from actual runs, which often hinder their ability to provide quick and clear performance predic…
Cross-BERT for Point Cloud Pretraining
Xin Li, Peng Li, Zeyong Wei +7
Introducing BERT into cross-modal settings raises difficulties in its optimization for handling multiple modalities. Both the BERT architecture and training objective need to be ad…
Don't worry about mistakes! Glass Segmentation Network via Mistake Correction
Chengyu Zheng, Peng Li, Xiao-Ping Zhang +2
Recall one time when we were in an unfamiliar mall. We might mistakenly think that there exists or does not exist a piece of glass in front of us. Such mistakes will remind us to w…
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…
iSmallNet: Densely Nested Network with Label Decoupling for Infrared Small Target Detection
Zhiheng Hu, Yongzhen Wang, Peng Li +3
Small targets are often submerged in cluttered backgrounds of infrared images. Conventional detectors tend to generate false alarms, while CNN-based detectors lose small targets in…