Search Results for author: Yongchuan Tang

Found 6 papers, 2 papers with code

TwinDiffusion: Enhancing Coherence and Efficiency in Panoramic Image Generation with Diffusion Models

no code implementations30 Apr 2024 Teng Zhou, Yongchuan Tang

Diffusion models have emerged as effective tools for generating diverse and high-quality content.

Image Generation

The negation of permutation mass function

no code implementations11 Mar 2024 Yongchuan Tang, Rongfei Li

As a generalization of evidence theory, random permutation sets theory may represent information more precisely.

Negation

Image Synthesis From Layout With Locality-Aware Mask Adaption

1 code implementation ICCV 2021 Zejian Li, Jingyu Wu, Immanuel Koh, Yongchuan Tang, Lingyun Sun

Object masks are generated separately and mapped to bounding boxes to form a whole semantic segmentation mask (layout-to-mask), with which a new image is generated (mask-to-image).

Image Generation Object +1

Combination of interval-valued belief structures based on belief entropy

no code implementations27 Nov 2020 Miao Qin, Yongchuan Tang

This paper investigates the issues of combination and normalization of interval-valued belief structures within the framework of Dempster-Shafer theory of evidence.

A new approach for generation of generalized basic probability assignment in the evidence theory

no code implementations6 Apr 2020 Dongdong Wu, Zijing Liu, Yongchuan Tang

To address multi-source information fusion problem, this paper considers the situation of uncertain information modeling from the closed world to the open world assumption and studies the generation of basic probability assignment (BPA) with incomplete information.

Unsupervised Disentangled Representation Learning with Analogical Relations

1 code implementation25 Apr 2018 Zejian Li, Yongchuan Tang, Yongxing He

The analogy is one of the typical cognitive processes, and our proposed strategy is based on the observation that sample pairs in which one is different from the other in one specific generative factor show the same analogical relation.

Disentanglement Relation

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