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20202026
most citedForget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models

12 citations · 70 across the 22 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.CV2022★ 1 cited

Image Completion with Heterogeneously Filtered Spectral Hints

Xingqian Xu, Shant Navasardyan, Vahram Tadevosyan +3

Image completion with large-scale free-form missing regions is one of the most challenging tasks for the computer vision community. While researchers pursue better solutions, drawb…

cs.CV2022★ 11 cited

Versatile Diffusion: Text, Images and Variations All in One Diffusion Model

Xingqian Xu, Zhangyang Wang, Eric Zhang +2

Recent advances in diffusion models have set an impressive milestone in many generation tasks, and trending works such as DALL-E2, Imagen, and Stable Diffusion have attracted great…

cs.CV2022★ 8 cited

Efficient Image Generation with Variadic Attention Heads

Steven Walton, Ali Hassani, Xingqian Xu +2

While the integration of transformers in vision models have yielded significant improvements on vision tasks they still require significant amounts of computation for both training…

cs.CV2022★ 2 cited

Towards Layer-wise Image Vectorization

Xu Ma, Yuqian Zhou, Xingqian Xu +5

Image rasterization is a mature technique in computer graphics, while image vectorization, the reverse path of rasterization, remains a major challenge. Recent advanced deep learni…

eess.IV2022★ 6 cited

VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolution

Zeyuan Chen, Yinbo Chen, Jingwen Liu +5

Videos typically record the streaming and continuous visual data as discrete consecutive frames. Since the storage cost is expensive for videos of high fidelity, most of them are s…