1 citations · 5 across the 18 of their papers we have counts for
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How Does Topology Bias Distort Message Passing? A Dirichlet Energy Perspective
Yanbiao Ji, Yue Ding, Dan Luo +4
Graph-based recommender systems have achieved remarkable effectiveness by modeling high-order interactions between users and items. However, such approaches are significantly under…
Discretized Gaussian Representation for Tomographic Reconstruction
Shaokai Wu, Yuxiang Lu, Yapan Guo +9
Computed Tomography (CT) enables detailed cross-sectional imaging but continues to face challenges in balancing reconstruction quality and computational efficiency. While deep lear…
From Anchors to Answers: A Novel Node Tokenizer for Integrating Graph Structure into Large Language Models
Yanbiao Ji, Chang Liu, Xin Chen +5
Enabling large language models (LLMs) to effectively process and reason with graph-structured data remains a significant challenge despite their remarkable success in natural langu…
Towards Personalized Federated Multi-Scenario Multi-Task Recommendation
Yue Ding, Yanbiao Ji, Xun Cai +7
In modern recommender systems, especially in e-commerce, predicting multiple targets such as click-through rate (CTR) and post-view conversion rate (CTCVR) is common. Multi-task re…
Learning Multiple Representations with Inconsistency-Guided Detail Regularization for Mask-Guided Matting
Weihao Jiang, Zhaozhi Xie, Yuxiang Lu +6
Mask-guided matting networks have achieved significant improvements and have shown great potential in practical applications in recent years. However, simply learning matting repre…
View-Centric Multi-Object Tracking with Homographic Matching in Moving UAV
Deyi Ji, Lanyun Zhu, Siqi Gao +8
In this paper, we address the challenge of Multi-Object Tracking (MOT) in moving Unmanned Aerial Vehicle (UAV) scenarios, where irregular flight trajectories, such as hovering, tur…
Task Indicating Transformer for Task-conditional Dense Predictions
Yuxiang Lu, Shalayiding Sirejiding, Bayram Bayramli +3
The task-conditional model is a distinctive stream for efficient multi-task learning. Existing works encounter a critical limitation in learning task-agnostic and task-specific rep…
YOLO-MED : Multi-Task Interaction Network for Biomedical Images
Suizhi Huang, Shalayiding Sirejiding, Yuxiang Lu +4
Object detection and semantic segmentation are pivotal components in biomedical image analysis. Current single-task networks exhibit promising outcomes in both detection and segmen…
Boosting Semi-Supervised 2D Human Pose Estimation by Revisiting Data Augmentation and Consistency Training
Huayi Zhou, Mukun Luo, Fei Jiang +3
The 2D human pose estimation (HPE) is a basic visual problem. However, its supervised learning requires massive keypoint labels, which is labor-intensive to collect. Thus, we aim a…
Enhancing cross-domain detection: adaptive class-aware contrastive transformer
Ziru Zeng, Yue Ding, Hongtao Lu
Recently,the detection transformer has gained substantial attention for its inherent minimal post-processing requirement.However,this paradigm relies on abundant training data,yet…
PA-SAM: Prompt Adapter SAM for High-Quality Image Segmentation
Zhaozhi Xie, Bochen Guan, Weihao Jiang +4
The Segment Anything Model (SAM) has exhibited outstanding performance in various image segmentation tasks. Despite being trained with over a billion masks, SAM faces challenges in…