Search Results for author: Yuxuan Ding

Found 6 papers, 2 papers with code

The CLIP Model is Secretly an Image-to-Prompt Converter

1 code implementation22 May 2023 Yuxuan Ding, Chunna Tian, Haoxuan Ding, Lingqiao Liu

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-Training (CLIP).


Position-Aware Relation Learning for RGB-Thermal Salient Object Detection

no code implementations21 Sep 2022 Heng Zhou, Chunna Tian, Zhenxi Zhang, Chengyang Li, Yuxuan Ding, Yongqiang Xie, Zhongbo Li

FRDF utilizes the directional information between object pixels to effectively enhance the intra-class compactness of salient regions.

object-detection Object Detection +1

Seeking Subjectivity in Visual Emotion Distribution Learning

no code implementations25 Jul 2022 Jingyuan Yang, Jie Li, Leida Li, Xiumei Wang, Yuxuan Ding, Xinbo Gao

In psychology, the \textit{Object-Appraisal-Emotion} model has demonstrated that each individual's emotion is affected by his/her subjective appraisal, which is further formed by the affective memory.

Emotion Recognition

Don't Stop Learning: Towards Continual Learning for the CLIP Model

no code implementations19 Jul 2022 Yuxuan Ding, Lingqiao Liu, Chunna Tian, Jingyuan Yang, Haoxuan Ding

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.

Continual Learning Image-text matching +2

Stimuli-Aware Visual Emotion Analysis

no code implementations4 Sep 2021 Jingyuan Yang, Jie Li, Xiumei Wang, Yuxuan Ding, Xinbo Gao

Then, we design three specific networks, i. e., Global-Net, Semantic-Net and Expression-Net, to extract distinct emotional features from different stimuli simultaneously.

Emotion Recognition

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