84 citations · 187 across the 6 of their papers we have counts for
6 papers
EZIGen: Enhancing zero-shot personalized image generation with precise subject encoding and decoupled guidance
Zicheng Duan, Yuxuan Ding, Chenhui Gou +3
Zero-shot personalized image generation models aim to produce images that align with both a given text prompt and subject image, requiring the model to incorporate both sources of…
The CLIP Model is Secretly an Image-to-Prompt Converter
Yuxuan Ding, Chunna Tian, Haoxuan Ding +1
The Stable Diffusion model is a prominent text-to-image generation model that relies on a text prompt as its input, which is encoded using the Contrastive Language-Image Pre-Traini…
Position-Aware Relation Learning for RGB-Thermal Salient Object Detection
Heng Zhou, Chunna Tian, Zhenxi Zhang +4
RGB-Thermal salient object detection (SOD) combines two spectra to segment visually conspicuous regions in images. Most existing methods use boundary maps to learn the sharp bounda…
Seeking Subjectivity in Visual Emotion Distribution Learning
Jingyuan Yang, Jie Li, Leida Li +3
Visual Emotion Analysis (VEA), which aims to predict people's emotions towards different visual stimuli, has become an attractive research topic recently. Rather than a single labe…
Don't Stop Learning: Towards Continual Learning for the CLIP Model
Yuxuan Ding, Lingqiao Liu, Chunna Tian +2
The Contrastive Language-Image Pre-training (CLIP) Model is a recently proposed large-scale pre-train model which attracts increasing attention in the computer vision community. Be…
Stimuli-Aware Visual Emotion Analysis
Jingyuan Yang, Jie Li, Xiumei Wang +2
Visual emotion analysis (VEA) has attracted great attention recently, due to the increasing tendency of expressing and understanding emotions through images on social networks. Dif…