6 citations · 6 across the 5 of their papers we have counts for
7 papers
MUSE: A Simple Yet Effective Multimodal Search-Based Framework for Lifelong User Interest Modeling
Bin Wu, Feifan Yang, Zhangming Chan +8
Lifelong user interest modeling is crucial for industrial recommender systems, yet existing approaches rely predominantly on ID-based features, suffering from poor generalization o…
Dual-level Modality Debiasing Learning for Unsupervised Visible-Infrared Person Re-Identification
Jiaze Li, Yan Lu, Bin Liu +2
Two-stage learning pipeline has achieved promising results in unsupervised visible-infrared person re-identification (USL-VI-ReID). It first performs single-modality learning and t…
FedThief: Harming Others to Benefit Oneself in Self-Centered Federated Learning
Xiangyu Zhang, Mang Ye
In federated learning, participants' uploaded model updates cannot be directly verified, leaving the system vulnerable to malicious attacks. Existing attack strategies have adversa…
Pose-Star: Anatomy-Aware Editing for Open-World Fashion Images
Yuran Dong, Mang Ye
To advance real-world fashion image editing, we analyze existing two-stage pipelines(mask generation followed by diffusion-based editing)which overly prioritize generator optimizat…
Scalable and Generalizable Correspondence Pruning via Geometry-Consistent Pre-training
Tangfei Liao, Xiaoqin Zhang, Tao Wang +4
Two-view correspondence pruning aims to identify reliable correspondences for camera pose estimation, serving as a fundamental step in many 3D vision tasks. Existing methods rely o…
Negative Pre-aware for Noisy Cross-modal Matching
Xu Zhang, Hao Li, Mang Ye
Cross-modal noise-robust learning is a challenging task since noisy correspondence is hard to recognize and rectify. Due to the cumulative and unavoidable negative impact of unreso…
Rethinking Client Drift in Federated Learning: A Logit Perspective
Yunlu Yan, Chun-Mei Feng, Mang Ye +5
Federated Learning (FL) enables multiple clients to collaboratively learn in a distributed way, allowing for privacy protection. However, the real-world non-IID data will lead to c…