26 citations · 28 across the 10 of their papers we have counts for
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DORS: Dynamic Attention Routing for Diffusion-based Object Removal in Dense Scenes
Haitong Tang, Haipeng Liu, Yang Wang
Object removal aims to eliminate target objects specified by a mask while preserving visual consistency with the surrounding regions. Existing methods typically rely on contextual…
Rare Concept Generation via Counterfactual Inference in Diffusion Models
Zhengyuan Jiang, Haipeng Liu, Meng Wang +1
Rare concept generation focuses on synthesizing customized images conditioned on text prompts that describe objects with unusual attributes. Previous works failed to align the gene…
STEDiff: Strengthening Text Embedding for Text-to-Image Alignment in Diffusion Model
Hailan Zhang, Haipeng Liu, Bo Fu +1
Although pretrained text-to-image (T2I) generation models can produce high-quality images, they often fail to faithfully reflect the semantic intent of complex prompts due to stoch…
AI-T2I: Aggregating-and-Isolating Cross-Attention to Diffusion Models for Text-to-Image Synthesis
Shipeng Cao, Biao Qian, Haipeng Liu +2
Text-to-image synthesis has made significant progress, benefiting from the strong generative capabilities of diffusion models. However, these models struggle to achieve precise tex…
Thinking inside the Convolution for Image Inpainting: Reconstructing Texture via Structure under Global and Local Side
Haipeng Liu, Yang Wang, Biao Qian +2
Image inpainting has earned substantial progress, owing to the encoder-and-decoder pipeline, which is benefited from the Convolutional Neural Networks (CNNs) with convolutional dow…
One Stone with Two Birds: A Null-Text-Null Frequency-Aware Diffusion Models for Text-Guided Image Inpainting
Haipeng Liu, Yang Wang, Meng Wang
Text-guided image inpainting aims at reconstructing the masked regions as per text prompts, where the longstanding challenges lie in the preservation for unmasked regions, while ac…