9 citations · 14 across the 8 of their papers we have counts for
9 papers
InpaintHuman: Reconstructing Occluded Humans with Multi-Scale UV Mapping and Identity-Preserving Diffusion Inpainting
Jinlong Fan, Shanshan Zhao, Liang Zheng +3
Reconstructing complete and animatable 3D human avatars from monocular videos remains challenging, particularly under severe occlusions. While 3D Gaussian Splatting has enabled pho…
Harnessing Text-to-Image Diffusion Models for Point Cloud Self-Supervised Learning
Yiyang Chen, Shanshan Zhao, Lunhao Duan +2
Diffusion-based models, widely used in text-to-image generation, have proven effective in 2D representation learning. Recently, this framework has been extended to 3D self-supervis…
Towards Modality-agnostic Label-efficient Segmentation with Entropy-Regularized Distribution Alignment
Liyao Tang, Zhe Chen, Shanshan Zhao +2
Label-efficient segmentation aims to perform effective segmentation on input data using only sparse and limited ground-truth labels for training. This topic is widely studied in 3D…
UniMix: Towards Domain Adaptive and Generalizable LiDAR Semantic Segmentation in Adverse Weather
Haimei Zhao, Jing Zhang, Zhuo Chen +2
LiDAR semantic segmentation (LSS) is a critical task in autonomous driving and has achieved promising progress. However, prior LSS methods are conventionally investigated and evalu…
Local-consistent Transformation Learning for Rotation-invariant Point Cloud Analysis
Yiyang Chen, Lunhao Duan, Shanshan Zhao +2
Rotation invariance is an important requirement for point shape analysis. To achieve this, current state-of-the-art methods attempt to construct the local rotation-invariant repres…
When ControlNet Meets Inexplicit Masks: A Case Study of ControlNet on its Contour-following Ability
Wenjie Xuan, Yufei Xu, Shanshan Zhao +4
ControlNet excels at creating content that closely matches precise contours in user-provided masks. However, when these masks contain noise, as a frequent occurrence with non-exper…
ConDaFormer: Disassembled Transformer with Local Structure Enhancement for 3D Point Cloud Understanding
Lunhao Duan, Shanshan Zhao, Nan Xue +3
Transformers have been recently explored for 3D point cloud understanding with impressive progress achieved. A large number of points, over 0.1 million, make the global self-attent…
Optical Quantum Sensing for Agnostic Environments via Deep Learning
Zeqiao Zhou, Yuxuan Du, Xu-Fei Yin +3
Optical quantum sensing promises measurement precision beyond classical sensors termed the Heisenberg limit (HL). However, conventional methodologies often rely on prior knowledge…
DeepSolo++: Let Transformer Decoder with Explicit Points Solo for Multilingual Text Spotting
Maoyuan Ye, Jing Zhang, Shanshan Zhao +4
End-to-end text spotting aims to integrate scene text detection and recognition into a unified framework. Dealing with the relationship between the two sub-tasks plays a pivotal ro…