Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- The University of MelbourneAU1.9k papers
- Centre National de la Recherche ScientifiqueFR1.9k papers
- The University of TokyoJP1.8k papers
- University of LjubljanaSI1.7k papers
- Chinese Academy of SciencesCN1.7k papers
- Nagoya UniversityJP1.7k papers
- University of Science and Technology of ChinaCN1.7k papers
- High Energy Accelerator Research OrganizationJP1.6k papers
- Institute of Nuclear Physics, Polish Academy of SciencesPL1.5k papers
- University of CambridgeGB1.5k papers
- Tokyo Institute of TechnologyJP1.5k papers
- University of OxfordGB1.4k papers
300 papers · 1 filter
SRENet: Spectral Re-Entry Network for Point Cloud Action Recognition
Qiuxia Wu, Jiarui Lan, Wenxiong Kang +2
Recognizing human actions from point cloud sequences is critical for 3D perception driven applications such as autonomous driving and human-computer interaction. However, the irreg…
Unsupervised Anomaly Detection in Brain MRI via Disentangled Anatomy Learning
Tao Yang, Xiuying Wang, Hao Liu +4
Detection of various lesions in brain MRI is clinically critical, but challenging due to the diversity of lesions and variability in imaging conditions. Current unsupervised learni…
Intersectional Fairness in Vision-Language Models for Medical Image Disease Classification
Yupeng Zhang, Adam G. Dunn, Usman Naseem +1
Medical artificial intelligence (AI) systems, particularly multimodal vision-language models (VLM), often exhibit intersectional biases where models are systematically less confide…
FedSC: Federated Learning with Semantic-Aware Collaboration
Huan Wang, Haoran Li, Huaming Chen +3
Federated learning (FL) aims to train models collaboratively across clients without sharing data for privacy-preserving. However, one major challenge is the data heterogeneity issu…
Improving Weakly Supervised Temporal Action Localization by Exploiting Multi-resolution Information in Temporal Domain
Rui Su, Dong Xu, Luping Zhou +1
Weakly supervised temporal action localization is a challenging task as only the video-level annotation is available during the training process. To address this problem, we propos…
MedCFVQA: A Causal Approach to Mitigate Modality Preference Bias in Medical Visual Question Answering
Shuchang Ye, Usman Naseem, Mingyuan Meng +2
Medical Visual Question Answering (MedVQA) is crucial for enhancing the efficiency of clinical diagnosis by providing accurate and timely responses to clinicians' inquiries regardi…
MIRROR: Multi-Modal Pathological Self-Supervised Representation Learning via Modality Alignment and Retention
Tianyi Wang, Jianan Fan, Dingxin Zhang +4
Histopathology and transcriptomics are fundamental modalities in oncology, encapsulating the morphological and molecular aspects of the disease. Multi-modal self-supervised learnin…
Using MRNet to Predict Lunar Rock Categories Detected by Chang'e 5 Probe
Jin Cui, Yifei Zou, Siyuan Zhang
China's Chang'e 5 mission has been a remarkable success, with the chang'e 5 lander traveling on the Oceanus Procellarum to collect images of the lunar surface. Over the past half c…
Towards End-to-End Neuromorphic Event-based 3D Object Reconstruction Without Physical Priors
Chuanzhi Xu, Langyi Chen, Haodong Chen +2
Neuromorphic cameras, also known as event cameras, are asynchronous brightness-change sensors that can capture extremely fast motion without suffering from motion blur, making them…
Hyper-Fusion Network for Semi-Automatic Segmentation of Skin Lesions
Lei Bi, Michael Fulham, Jinman Kim
Automatic skin lesion segmentation methods based on fully convolutional networks (FCNs) are regarded as the state-of-the-art for accuracy. When there are, however, insufficient tra…
NeRF-NQA: No-Reference Quality Assessment for Scenes Generated by NeRF and Neural View Synthesis Methods
Qiang Qu, Hanxue Liang, Xiaoming Chen +2
Neural View Synthesis (NVS) has demonstrated efficacy in generating high-fidelity dense viewpoint videos using a image set with sparse views. However, existing quality assessment m…
EvRepSL: Event-Stream Representation via Self-Supervised Learning for Event-Based Vision
Qiang Qu, Xiaoming Chen, Yuk Ying Chung +1
Event-stream representation is the first step for many computer vision tasks using event cameras. It converts the asynchronous event-streams into a formatted structure so that conv…
Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignments
Mingjian Li, Mingyuan Meng, Shuchang Ye +4
Medical image segmentation is a fundamental task in numerous medical engineering applications. Recently, language-guided segmentation has shown promise in medical scenarios where t…
Resource-Efficient Multiview Perception: Integrating Semantic Masking with Masked Autoencoders
Kosta Dakic, Kanchana Thilakarathna, Rodrigo N. Calheiros +1
Multiview systems have become a key technology in modern computer vision, offering advanced capabilities in scene understanding and analysis. However, these systems face critical c…
SGSeg: Enabling Text-free Inference in Language-guided Segmentation of Chest X-rays via Self-guidance
Shuchang Ye, Mingyuan Meng, Mingjian Li +2
Segmentation of infected areas in chest X-rays is pivotal for facilitating the accurate delineation of pulmonary structures and pathological anomalies. Recently, multi-modal langua…
Unleashing the Power of Generic Segmentation Models: A Simple Baseline for Infrared Small Target Detection
Mingjin Zhang, Chi Zhang, Qiming Zhang +3
Recent advancements in deep learning have greatly advanced the field of infrared small object detection (IRSTD). Despite their remarkable success, a notable gap persists between th…
Radio Frequency Signal based Human Silhouette Segmentation: A Sequential Diffusion Approach
Penghui Wen, Kun Hu, Dong Yuan +3
Radio frequency (RF) signals have been proved to be flexible for human silhouette segmentation (HSS) under complex environments. Existing studies are mainly based on a one-shot app…
TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Interpretable Sex and Age Prediction from Diffusion MRI Tractography
Yuqian Chen, Fan Zhang, Meng Wang +10
The relationship between brain connections and non-imaging phenotypes is increasingly studied using deep neural networks. However, the local and global properties of brain white ma…
RU-AI: A Large Multimodal Dataset for Machine-Generated Content Detection
Liting Huang, Zhihao Zhang, Yiran Zhang +2
The recent generative AI models' capability of creating realistic and human-like content is significantly transforming the ways in which people communicate, create and work. The ma…
Motion Keyframe Interpolation for Any Human Skeleton via Temporally Consistent Point Cloud Sampling and Reconstruction
Clinton Mo, Kun Hu, Chengjiang Long +2
In the character animation field, modern supervised keyframe interpolation models have demonstrated exceptional performance in constructing natural human motions from sparse pose d…
BenthicNet: A global compilation of seafloor images for deep learning applications
Scott C. Lowe, Benjamin Misiuk, Isaac Xu +26
Advances in underwater imaging enable collection of extensive seafloor image datasets necessary for monitoring important benthic ecosystems. The ability to collect seafloor imagery…
Cross-domain Fiber Cluster Shape Analysis for Language Performance Cognitive Score Prediction
Yui Lo, Yuqian Chen, Dongnan Liu +8
Shape plays an important role in computer graphics, offering informative features to convey an object's morphology and functionality. Shape analysis in brain imaging can help inter…
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…
Multi-source-free Domain Adaptation via Uncertainty-aware Adaptive Distillation
Yaxuan Song, Jianan Fan, Dongnan Liu +1
Source-free domain adaptation (SFDA) alleviates the domain discrepancy among data obtained from domains without accessing the data for the awareness of data privacy. However, exist…