9 citations · 29 across the 21 of their papers we have counts for
22 papers
TAU-Bench: From Anomaly Instance Tracking to Fine-Grained Video Anomaly Understanding
Kepeng Yang, Dongxuan Liu, Rongxin Gao +8
Humans understand anomalous events through a coherent perceptual process in which they identify the focal instance, follow its behavior as the event unfolds, and interpret why it v…
Harnessing Lightweight Transformer with Contextual Synergic Enhancement for Efficient 3D Medical Image Segmentation
Xinyu Liu, Zhen Chen, Wuyang Li +2
Transformers have shown remarkable performance in 3D medical image segmentation, but their high computational requirements and need for large amounts of labeled data limit their ap…
MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learning
Shengyuan Liu, Liuxin Bao, Qi Yang +6
Medical image segmentation is evolving from task-specific models toward generalizable frameworks. Recent research leverages Multi-modal Large Language Models (MLLMs) as autonomous…
FedGPS: Statistical Rectification Against Data Heterogeneity in Federated Learning
Zhiqin Yang, Yonggang Zhang, Chenxin Li +3
Federated Learning (FL) confronts a significant challenge known as data heterogeneity, which impairs model performance and convergence. Existing methods have made notable progress…
MetaScope: Optics-Driven Neural Network for Ultra-Micro Metalens Endoscopy
Wuyang Li, Wentao Pan, Xiaoyuan Liu +6
Miniaturized endoscopy has advanced accurate visual perception within the human body. Prevailing research remains limited to conventional cameras employing convex lenses, where the…
WonderFree: Enhancing Novel View Quality and Cross-View Consistency for 3D Scene Exploration
Chaojun Ni, Jie Li, Haoyun Li +8
Interactive 3D scene generation from a single image has gained significant attention due to its potential to create immersive virtual worlds. However, a key challenge in current 3D…
Track Any Anomalous Object: A Granular Video Anomaly Detection Pipeline
Yuzhi Huang, Chenxin Li, Haitao Zhang +9
Video anomaly detection (VAD) is crucial in scenarios such as surveillance and autonomous driving, where timely detection of unexpected activities is essential. Although existing m…
FlexGS: Train Once, Deploy Everywhere with Many-in-One Flexible 3D Gaussian Splatting
Hengyu Liu, Yuehao Wang, Chenxin Li +6
3D Gaussian splatting (3DGS) has enabled various applications in 3D scene representation and novel view synthesis due to its efficient rendering capabilities. However, 3DGS demands…
Towards a general-purpose foundation model for fMRI analysis
Cheng Wang, Yu Jiang, Zhihao Peng +18
Functional MRI (fMRI) is crucial for studying brain function and diagnosing neurological disorders. However, existing analysis methods suffer from reproducibility and transferabili…
X-GRM: Large Gaussian Reconstruction Model for Sparse-view X-rays to Computed Tomography
Yifan Liu, Wuyang Li, Weihao Yu +4
Computed Tomography serves as an indispensable tool in clinical workflows, providing non-invasive visualization of internal anatomical structures. Existing CT reconstruction works…
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…
JarvisIR: Elevating Autonomous Driving Perception with Intelligent Image Restoration
Yunlong Lin, Zixu Lin, Haoyu Chen +6
Vision-centric perception systems struggle with unpredictable and coupled weather degradations in the wild. Current solutions are often limited, as they either depend on specific d…
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…
X-Gaussian: 4D Radiative Gaussian Splatting for Continuous-time Tomographic Reconstruction
Weihao Yu, Yuanhao Cai, Ruyi Zha +3
Four-dimensional computed tomography (4D CT) reconstruction is crucial for capturing dynamic anatomical changes but faces inherent limitations from conventional phase-binning workf…
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…
AutoPET Challenge: Tumour Synthesis for Data Augmentation
Lap Yan Lennon Chan, Chenxin Li, Yixuan Yuan
Accurate lesion segmentation in whole-body PET/CT scans is crucial for cancer diagnosis and treatment planning, but limited datasets often hinder the performance of automated segme…
NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei Segmentation
Zhenye Lou, Qing Xu, Zekun Jiang +6
Domain-generalized nuclei segmentation refers to the generalizability of models to unseen domains based on knowledge learned from source domains and is challenged by various image…
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…
De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation
Qing Xu, Jiaxuan Li, Xiangjian He +8
The universality of deep neural networks across different modalities and their generalization capabilities to unseen domains play an essential role in medical image segmentation. T…
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…
Knowledge Condensation Distillation
Chenxin Li, Mingbao Lin, Zhiyuan Ding +5
Knowledge Distillation (KD) transfers the knowledge from a high-capacity teacher network to strengthen a smaller student. Existing methods focus on excavating the knowledge hints a…
Generator Versus Segmentor: Pseudo-healthy Synthesis
Zhang Yunlong, Li Chenxin, Lin Xin +6
This paper investigates the problem of pseudo-healthy synthesis that is defined as synthesizing a subject-specific pathology-free image from a pathological one. Recent approaches b…