21 citations · 74 across the 14 of their papers we have counts for
12 papers · 1 filter
Seeing is Improving: Visual Feedback for Iterative Text Layout Refinement
Junrong Guo, Shancheng Fang, Yadong Qu +1
Recent advances in Multimodal Large Language Models (MLLMs) have enabled automated generation of structured layouts from natural language descriptions. Existing methods typically f…
IGD: Instructional Graphic Design with Multimodal Layer Generation
Yadong Qu, Shancheng Fang, Yuxin Wang +4
Graphic design visually conveys information and data by creating and combining text, images and graphics. Two-stage methods that rely primarily on layout generation lack creativity…
MaskDiT: Dual Mask-based Diffusion Transformer for Multi-Scene Long Video Generation
Tianhao Qi, Jianlong Yuan, Wanquan Feng +6
Sora has unveiled the immense potential of the Diffusion Transformer (DiT) architecture in single-scene video generation. However, the more challenging task of multi-scene video ge…
Sentiment-oriented Transformer-based Variational Autoencoder Network for Live Video Commenting
Fengyi Fu, Shancheng Fang, Weidong Chen +1
Automatic live video commenting is with increasing attention due to its significance in narration generation, topic explanation, etc. However, the diverse sentiment consideration o…
DEADiff: An Efficient Stylization Diffusion Model with Disentangled Representations
Tianhao Qi, Shancheng Fang, Yanze Wu +5
The diffusion-based text-to-image model harbors immense potential in transferring reference style. However, current encoder-based approaches significantly impair the text controlla…
DreamIdentity: Improved Editability for Efficient Face-identity Preserved Image Generation
Zhuowei Chen, Shancheng Fang, Wei Liu +4
While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centric images, an intractable problem is how to preserve the face identity for con…
Design Booster: A Text-Guided Diffusion Model for Image Translation with Spatial Layout Preservation
Shiqi Sun, Shancheng Fang, Qian He +1
Diffusion models are able to generate photorealistic images in arbitrary scenes. However, when applying diffusion models to image translation, there exists a trade-off between main…
ABINet++: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Spotting
Shancheng Fang, Zhendong Mao, Hongtao Xie +3
Scene text spotting is of great importance to the computer vision community due to its wide variety of applications. Recent methods attempt to introduce linguistic knowledge for ch…
CDistNet: Perceiving Multi-Domain Character Distance for Robust Text Recognition
Tianlun Zheng, Zhineng Chen, Shancheng Fang +2
The Transformer-based encoder-decoder framework is becoming popular in scene text recognition, largely because it naturally integrates recognition clues from both visual and semant…
From Two to One: A New Scene Text Recognizer with Visual Language Modeling Network
Yuxin Wang, Hongtao Xie, Shancheng Fang +3
In this paper, we abandon the dominant complex language model and rethink the linguistic learning process in the scene text recognition. Different from previous methods considering…
PERT: A Progressively Region-based Network for Scene Text Removal
Yuxin Wang, Hongtao Xie, Shancheng Fang +2
Scene text removal (STR) contains two processes: text localization and background reconstruction. Through integrating both processes into a single network, previous methods provide…
Read Like Humans: Autonomous, Bidirectional and Iterative Language Modeling for Scene Text Recognition
Shancheng Fang, Hongtao Xie, Yuxin Wang +2
Linguistic knowledge is of great benefit to scene text recognition. However, how to effectively model linguistic rules in end-to-end deep networks remains a research challenge. In…