8 citations · 21 across the 12 of their papers we have counts for
11 papers · 1 filter
WorldMirror: Universal 3D World Reconstruction with Any-Prior Prompting
Yifan Liu, Zhiyuan Min, Zhenwei Wang +5
We present WorldMirror, a unified feed-forward model for comprehensive 3D geometric prediction tasks. Unlike existing methods constrained to image-only inputs or customized for a s…
MonoSplat: Generalizable 3D Gaussian Splatting from Monocular Depth Foundation Models
Yifan Liu, Keyu Fan, Weihao Yu +3
Recent advances in generalizable 3D Gaussian Splatting have demonstrated promising results in real-time high-fidelity rendering without per-scene optimization, yet existing approac…
GeoT: Geometry-guided Instance-dependent Transition Matrix for Semi-supervised Tooth Point Cloud Segmentation
Weihao Yu, Xiaoqing Guo, Chenxin Li +2
Achieving meticulous segmentation of tooth point clouds from intra-oral scans stands as an indispensable prerequisite for various orthodontic applications. Given the labor-intensiv…
ConcealGS: Concealing Invisible Copyright Information in 3D Gaussian Splatting
Yifeng Yang, Hengyu Liu, Chenxin Li +6
With the rapid development of 3D reconstruction technology, the widespread distribution of 3D data has become a future trend. While traditional visual data (such as images and vide…
When 3D Partial Points Meets SAM: Tooth Point Cloud Segmentation with Sparse Labels
Yifan Liu, Wuyang Li, Cheng Wang +2
Tooth point cloud segmentation is a fundamental task in many orthodontic applications. Current research mainly focuses on fully supervised learning which demands expensive and tedi…
GTP-4o: Modality-prompted Heterogeneous Graph Learning for Omni-modal Biomedical Representation
Chenxin Li, Xinyu Liu, Cheng Wang +4
Recent advances in learning multi-modal representation have witnessed the success in biomedical domains. While established techniques enable handling multi-modal information, the c…
GaussianStego: A Generalizable Stenography Pipeline for Generative 3D Gaussians Splatting
Chenxin Li, Hengyu Liu, Zhiwen Fan +4
Recent advancements in large generative models and real-time neural rendering using point-based techniques pave the way for a future of widespread visual data distribution through…
EndoSparse: Real-Time Sparse View Synthesis of Endoscopic Scenes using Gaussian Splatting
Chenxin Li, Brandon Y. Feng, Yifan Liu +4
3D reconstruction of biological tissues from a collection of endoscopic images is a key to unlock various important downstream surgical applications with 3D capabilities. Existing…
LGS: A Light-weight 4D Gaussian Splatting for Efficient Surgical Scene Reconstruction
Hengyu Liu, Yifan Liu, Chenxin Li +2
The advent of 3D Gaussian Splatting (3D-GS) techniques and their dynamic scene modeling variants, 4D-GS, offers promising prospects for real-time rendering of dynamic surgical scen…
Endora: Video Generation Models as Endoscopy Simulators
Chenxin Li, Hengyu Liu, Yifan Liu +6
Generative models hold promise for revolutionizing medical education, robot-assisted surgery, and data augmentation for machine learning. Despite progress in generating 2D medical…
EndoGaussian: Real-time Gaussian Splatting for Dynamic Endoscopic Scene Reconstruction
Yifan Liu, Chenxin Li, Chen Yang +1
Reconstructing deformable tissues from endoscopic videos is essential in many downstream surgical applications. However, existing methods suffer from slow rendering speed, greatly…