111 citations · 128 across the 13 of their papers we have counts for
10 papers · 1 filter
SceneBooth: Diffusion-based Framework for Subject-preserved Text-to-Image Generation
Shang Chai, Zihang Lin, Min Zhou +3
Due to the demand for personalizing image generation, subject-driven text-to-image generation method, which creates novel renditions of an input subject based on text prompts, has…
Flatness Guided Test-Time Adaptation for Vision-Language Models
Aodi Li, Liansheng Zhuang, Xiao Long +2
Test-time adaptation (TTA) of Vision-Language Models (VLMs) has emerged as a technique for tackling distribution shifts during the test time. Recent research indicates that the tes…
Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes
Aodi Li, Liansheng Zhuang, Xiao Long +2
Domain generalization aims to learn a model from multiple training domains and generalize it to unseen test domains. Recent theory has shown that seeking the deep models, whose par…
LayoutDM: Transformer-based Diffusion Model for Layout Generation
Shang Chai, Liansheng Zhuang, Fengying Yan
Automatic layout generation that can synthesize high-quality layouts is an important tool for graphic design in many applications. Though existing methods based on generative model…
Private Gradient Estimation is Useful for Generative Modeling
Bochao Liu, Pengju Wang, Weijia Guo +4
While generative models have proved successful in many domains, they may pose a privacy leakage risk in practical deployment. To address this issue, differentially private generati…
Estimation of Reliable Proposal Quality for Temporal Action Detection
Junshan Hu, Chaoxu guo, Liansheng Zhuang +4
Temporal action detection (TAD) aims to locate and recognize the actions in an untrimmed video. Anchor-free methods have made remarkable progress which mainly formulate TAD into tw…
One-shot Key Information Extraction from Document with Deep Partial Graph Matching
Minghong Yao, Zhiguang Liu, Liangwei Wang +2
Automating the Key Information Extraction (KIE) from documents improves efficiency, productivity, and security in many industrial scenarios such as rapid indexing and archiving. Ma…
Graph Construction with Label Information for Semi-Supervised Learning
Liansheng Zhuang, Zihan Zhou, Jingwen Yin +4
In the literature, most existing graph-based semi-supervised learning (SSL) methods only use the label information of observed samples in the label propagation stage, while ignorin…
Constructing a Non-Negative Low Rank and Sparse Graph with Data-Adaptive Features
Liansheng Zhuang, Shenghua Gao, Jinhui Tang +3
This paper aims at constructing a good graph for discovering intrinsic data structures in a semi-supervised learning setting. Firstly, we propose to build a non-negative low-rank a…
Sparse Illumination Learning and Transfer for Single-Sample Face Recognition with Image Corruption and Misalignment
Liansheng Zhuang, Tsung-Han Chan, Allen Y. Yang +2
Single-sample face recognition is one of the most challenging problems in face recognition. We propose a novel algorithm to address this problem based on a sparse representation ba…