1.3k citations · 1.3k across the 9 of their papers we have counts for
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PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control
Ruichen Wang, Junliang Zhang, Qingsong Xie +2
Recently, diffusion models have exhibited superior performance in the area of image inpainting. Inpainting methods based on diffusion models can usually generate realistic, high-qu…
When are Foundation Models Effective? Understanding the Suitability for Pixel-Level Classification Using Multispectral Imagery
Yiqun Xie, Zhihao Wang, Weiye Chen +7
Foundation models, i.e., very large deep learning models, have demonstrated impressive performances in various language and vision tasks that are otherwise difficult to reach using…
Towards Language-guided Interactive 3D Generation: LLMs as Layout Interpreter with Generative Feedback
Yiqi Lin, Hao Wu, Ruichen Wang +4
Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within…
Edit Everything: A Text-Guided Generative System for Images Editing
Defeng Xie, Ruichen Wang, Jian Ma +5
We introduce a new generative system called Edit Everything, which can take image and text inputs and produce image outputs. Edit Everything allows users to edit images using simpl…
GlyphDraw: Seamlessly Rendering Text with Intricate Spatial Structures in Text-to-Image Generation
Jian Ma, Mingjun Zhao, Chen Chen +4
Recent breakthroughs in the field of language-guided image generation have yielded impressive achievements, enabling the creation of high-quality and diverse images based on user i…