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Tianyang Shi

7 accepted papers

2023

ASM: Adaptive Skinning Model for High-Quality 3D Face Modeling

ICCV 2023poster

The research fields of parametric face model and 3D face reconstruction have been extensively studied. However, a critical question remains unanswered: how to tailor the face model for specific reconstruction settings. We argue that reconstruction with multi-view uncalibrated images demands a new mo…

Cited by 6PDFScholar
2021

Automatic Translation of Music-to-Dance for In-Game Characters

IJCAI 2021poster

Music-to-dance translation is an emerging and powerful feature in recent role-playing games. Previous works of this topic consider music-to-dance as a supervised motion generation problem based on time-series data. However, these methods require a large amount of training data pairs and may suffer f…

2021

Multi-View 3D Reconstruction With Transformers

ICCV 2021poster

Deep CNN-based methods have so far achieved the state of the art results in multi-view 3D object reconstruction. Despite the considerable progress, the two core modules of these methods - view feature extraction and multi-view fusion, are usually investigated separately, and the relations among mult…

Cited by 126PDFScholar
2020

Deep Adversarial Decomposition: A Unified Framework for Separating Superimposed Images

CVPR 2020poster

Separating individual image layers from a single mixed image has long been an important but challenging task. We propose a unified framework named "deep adversarial decomposition" for single superimposed image separation. Our method deals with both linear and non-linear mixtures under an adversarial…

Cited by 86PDFScholar
2019

Face-to-Parameter Translation for Game Character Auto-Creation

ICCV 2019poster

Character customization system is an important component in Role-Playing Games (RPGs), where players are allowed to edit the facial appearance of their in-game characters with their own preferences rather than using default templates. This paper proposes a method for automatically creating in-game c…

Cited by 75PDFScholar
2019

Generative Adversarial Training for Weakly Supervised Cloud Matting

ICCV 2019poster

The detection and removal of cloud in remote sensing images are essential for earth observation applications. Most previous methods consider cloud detection as a pixel-wise semantic segmentation process (cloud v.s. background), which inevitably leads to a category-ambiguity problem when dealing with…

Cited by 42PDFScholar