activity
20232026
most citedA User-Friendly Framework for Generating Model-Preferred Prompts in Text-to-Image Synthesis

9 citations · 10 across the 6 of their papers we have counts for

collaborators

6 papers

cs.GR2026

Screen, Cache, and Match: A Training-Free Causality-Consistent Reference Frame Framework for Human Animation

Jianan Wang, Nailei Hei, Li He +8

Human animation aims to generate temporally coherent and visually consistent videos over long sequences, yet modeling long-range dependencies while preserving frame quality remains…

cs.CV2025

Collaborative Reconstruction and Repair for Multi-class Industrial Anomaly Detection

Qishan Wang, Haofeng Wang, Shuyong Gao +5

Industrial anomaly detection is a challenging open-set task that aims to identify unknown anomalous patterns deviating from normal data distribution. To avoid the significant memor…

cs.CV2025

Search is All You Need for Few-shot Anomaly Detection

Qishan Wang, Jia Guo, Shuyong Gao +5

Few-shot anomaly detection (FSAD) has emerged as a crucial yet challenging task in industrial inspection, where normal distribution modeling must be accomplished with only a few no…

cs.MM2024★ 9 cited

A User-Friendly Framework for Generating Model-Preferred Prompts in Text-to-Image Synthesis

Nailei Hei, Qianyu Guo, Zihao Wang +3

Well-designed prompts have demonstrated the potential to guide text-to-image models in generating amazing images. Although existing prompt engineering methods can provide high-leve…

cs.SE2024★ 1 cited

KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation

Wei Tao, Yucheng Zhou, Yanlin Wang +3

Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods…

cs.CV2023

Plug-and-Play Feature Generation for Few-Shot Medical Image Classification

Qianyu Guo, Huifang Du, Xing Jia +4

Few-shot learning (FSL) presents immense potential in enhancing model generalization and practicality for medical image classification with limited training data; however, it still…