activity
20242026
collaborators

11 papers

cs.CV2026

MediRound: Multi-Round Entity-Level Reasoning Segmentation in Medical Images

Qinyue Tong, Ziqian Lu, Jun Liu +3

Despite notable progress in text-guided medical image segmentation nowadays, these methods are limited to single-round dialogues and fail to support multi-round reasoning, which is…

cs.CV2026

MedVeriSeg: Teaching LISA-Like Medical Segmentation Models to Verify Query Validity Without Extra Training

Qinyue Tong, Xiaozhen Wang, Ziqian Lu +3

Despite recent progress in text-prompt-based medical image segmentation, existing LISA-like MLLM-based methods typically generate masks regardless of whether the target specified i…

cs.LG2026

Multivariate Time Series Anomaly Detection via Dual-Branch Reconstruction and Autoregressive Flow-based Residual Density Estimation

Jun Liu, Ying Chen, Ziqian Lu +2

Multivariate Time Series Anomaly Detection (MTSAD) is critical for real-world monitoring scenarios such as industrial control and aerospace systems. Mainstream reconstruction-based…

cs.CV2026

Improving Anomaly Detection with Foundation-Model Synthesis and Wavelet-Domain Attention

Wensheng Wu, Zheming Lu, Ziqian Lu +5

Industrial anomaly detection faces significant challenges due to the scarcity of anomalous samples and the complexity of real-world anomalies. In this paper, we propose a foundatio…

cs.CV2025

Unlocking the Forgery Detection Potential of Vanilla MLLMs: A Novel Training-Free Pipeline

Rui Zuo, Qinyue Tong, Zhe-Ming Lu +1

With the rapid advancement of artificial intelligence-generated content (AIGC) technologies, including multimodal large language models (MLLMs) and diffusion models, image generati…

cs.CV2025

Accurate and lightweight dehazing via multi-receptive-field non-local network and novel contrastive regularization

Zewei He, Zixuan Chen, Jinlei Li +5

Recently, deep learning-based methods have dominated image dehazing domain. A multi-receptive-field non-local network (MRFNLN) consisting of the multi-stream feature attention bloc…