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20222026
most citedTowards Coherent Image Inpainting Using Denoising Diffusion Implicit Models

17 citations · 64 across the 34 of their papers we have counts for

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cs.CV2025

Learning from Online Videos at Inference Time for Computer-Use Agents

Yujian Liu, Ze Wang, Hao Chen +7

Computer-use agents can operate computers and automate laborious tasks, but despite recent rapid progress, they still lag behind human users, especially when tasks require domain-s…

cs.CV2023

Correcting Diffusion Generation through Resampling

Yujian Liu, Yang Zhang, Tommi Jaakkola +1

Despite diffusion models' superior capabilities in modeling complex distributions, there are still non-trivial distributional discrepancies between generated and ground-truth image…

cs.CV2023★ 6 cited

Improving Diffusion Models for Scene Text Editing with Dual Encoders

Jiabao Ji, Guanhua Zhang, Zhaowen Wang +4

Scene text editing is a challenging task that involves modifying or inserting specified texts in an image while maintaining its natural and realistic appearance. Most previous appr…

cs.CV2023★ 4 cited

Harnessing the Spatial-Temporal Attention of Diffusion Models for High-Fidelity Text-to-Image Synthesis

Qiucheng Wu, Yujian Liu, Handong Zhao +4

Diffusion-based models have achieved state-of-the-art performance on text-to-image synthesis tasks. However, one critical limitation of these models is the low fidelity of generate…

cs.CV2023★ 17 cited

Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models

Guanhua Zhang, Jiabao Ji, Yang Zhang +3

Image inpainting refers to the task of generating a complete, natural image based on a partially revealed reference image. Recently, many research interests have been focused on ad…