Search Results for author: Yong Tang

Found 13 papers, 5 papers with code

RealCompo: Dynamic Equilibrium between Realism and Compositionality Improves Text-to-Image Diffusion Models

2 code implementations20 Feb 2024 Xinchen Zhang, Ling Yang, Yaqi Cai, Zhaochen Yu, Jiake Xie, Ye Tian, Minkai Xu, Yong Tang, Yujiu Yang, Bin Cui

In this paper, we propose a new training-free and transferred-friendly text-to-image generation framework, namely RealCompo, which aims to leverage the advantages of text-to-image and layout-to-image models to enhance both realism and compositionality of the generated images.

Denoising Text-to-Image Generation

AllSpark: A Multimodal Spatio-Temporal General Intelligence Model with Thirteen Modalities

no code implementations31 Dec 2023 Run Shao, Cheng Yang, Qiujun Li, Qing Zhu, Yongjun Zhang, Yansheng Li, Yu Liu, Yong Tang, Dapeng Liu, Shizhong Yang, Haifeng Li

We introduce the Language as Reference Framework (LaRF), a fundamental principle for constructing a multimodal unified model, aiming to strike a trade-off between the cohesion and autonomy among different modalities.

Privileged Prior Information Distillation for Image Matting

no code implementations25 Nov 2022 Cheng Lyu, Jiake Xie, Bo Xu, Cheng Lu, Han Huang, Xin Huang, Ming Wu, Chuang Zhang, Yong Tang

Performance of trimap-free image matting methods is limited when trying to decouple the deterministic and undetermined regions, especially in the scenes where foregrounds are semantically ambiguous, chromaless, or high transmittance.

Image Matting

Efficient Multi-view Clustering via Unified and Discrete Bipartite Graph Learning

1 code implementation9 Sep 2022 Si-Guo Fang, Dong Huang, Xiao-Sha Cai, Chang-Dong Wang, Chaobo He, Yong Tang

By simultaneously formulating the view-specific bipartite graph learning, the view-consensus bipartite graph learning, and the discrete cluster structure learning into a unified objective function, an efficient minimization algorithm is then designed to tackle this optimization problem and directly achieve a discrete clustering solution without requiring additional partitioning, which notably has linear time complexity in data size.

Clustering Graph Learning

Situational Perception Guided Image Matting

no code implementations20 Apr 2022 Bo Xu, Jiake Xie, Han Huang, Ziwen Li, Cheng Lu, Yong Tang, Yandong Guo

In this paper, we propose a Situational Perception Guided Image Matting (SPG-IM) method that mitigates subjective bias of matting annotations and captures sufficient situational perception information for better global saliency distilled from the visual-to-textual task.

Image Matting Object

Joint Multi-view Unsupervised Feature Selection and Graph Learning

1 code implementation18 Apr 2022 Si-Guo Fang, Dong Huang, Chang-Dong Wang, Yong Tang

Second, they often learn the similarity structure by either global structure learning or local structure learning, which lack the capability of graph learning with both global and local structural awareness.

feature selection Graph Learning

GANet: Glyph-Attention Network for Few-Shot Font Generation

no code implementations29 Sep 2021 Mingtao Guo, Wei Xiong, Zheng Wang, Yong Tang, Ting Wu

Font generation is a valuable but challenging task, it is time consuming and costly to design font libraries which cover all glyphs with various styles.

Font Generation

ExamGAN and Twin-ExamGAN for Exam Script Generation

no code implementations22 Aug 2021 Zhengyang Wu, Ke Deng, Judy Qiu, Yong Tang

There are opportunities to further improve the quality of generated exam scripts in various aspects.

Generative Adversarial Network Management

Tripartite Information Mining and Integration for Image Matting

1 code implementation ICCV 2021 Yuhao Liu, Jiake Xie, Xiao Shi, Yu Qiao, Yujie Huang, Yong Tang, Xin Yang

Regarding the nature of image matting, most researches have focused on solutions for transition regions.

2k Image Matting

Modal-aware Features for Multimodal Hashing

no code implementations19 Nov 2019 Haien Zeng, Hanjiang Lai, Hanlu Chu, Yong Tang, Jian Yin

The modal-aware operation consists of a kernel network and an attention network.


An Interactive Insight Identification and Annotation Framework for Power Grid Pixel Maps using DenseU-Hierarchical VAE

no code implementations22 May 2019 Tianye Zhang, Haozhe Feng, Zexian Chen, Can Wang, Yanhao Huang, Yong Tang, Wei Chen

Insights in power grid pixel maps (PGPMs) refer to important facility operating states and unexpected changes in the power grid.

Dense Adaptive Cascade Forest: A Self Adaptive Deep Ensemble for Classification Problems

no code implementations29 Apr 2018 Haiyang Wang, Yong Tang, Ziyang Jia, Fei Ye

Second, our model connects each layer to the subsequent ones in a feed-forward fashion, which enhances the capability of the model to resist performance degeneration.

Ensemble Learning General Classification

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