collaborators

10 papers

cs.CV2026

TALENT: Target-aware Efficient Tuning for Referring Image Segmentation

Shuo Jin, Siyue Yu, Bingfeng Zhang +3

Referring image segmentation aims to segment specific targets based on a natural text expression. Recently, parameter-efficient tuning (PET) has emerged as a promising paradigm. Ho…

cs.CV2026

TF-SSD: A Strong Pipeline via Synergic Mask Filter for Training-free Co-salient Object Detection

Zhijin He, Shuo Jin, Siyue Yu +4

Co-salient Object Detection (CoSOD) aims to segment salient objects that consistently appear across a group of related images. Despite the notable progress achieved by recent train…

cs.IR2026

LLM-Enhanced Multimodal Fusion for Cross-Domain Sequential Recommendation

Wangyu Wu, Zhenhong Chen, Wenqiao Zhang +5

Cross-Domain Sequential Recommendation (CDSR) predicts user behavior by leveraging historical interactions across multiple domains, focusing on modeling cross-domain preferences an…

cs.CV2025

SynthSeg-Agents: Multi-Agent Synthetic Data Generation for Zero-Shot Weakly Supervised Semantic Segmentation

Wangyu Wu, Zhenhong Chen, Xiaowei Huang +2

Weakly Supervised Semantic Segmentation (WSSS) with image level labels aims to produce pixel level predictions without requiring dense annotations. While recent approaches have lev…

cs.CV2025

Tag-Enriched Multi-Attention with Large Language Models for Cross-Domain Sequential Recommendation

Wangyu Wu, Xuhang Chen, Zhenhong Chen +5

Cross-Domain Sequential Recommendation (CDSR) plays a crucial role in modern consumer electronics and e-commerce platforms, where users interact with diverse services such as books…

cs.CV2025

Contrastive Prompt Clustering for Weakly Supervised Semantic Segmentation

Wangyu Wu, Zhenhong Chen, Xiaowen Ma +6

Weakly Supervised Semantic Segmentation (WSSS) with image-level labels has gained attention for its cost-effectiveness. Most existing methods emphasize inter-class separation, ofte…