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20182023
most citedDual Aggregation Transformer for Image Super-Resolution

19 citations · 32 across the 3 of their papers we have counts for

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5 papers · 1 filter

cs.CV202319 cited

Dual Aggregation Transformer for Image Super-Resolution

Zheng Chen, Yulun Zhang, Jinjin Gu +3

Transformer has recently gained considerable popularity in low-level vision tasks, including image super-resolution (SR). These networks utilize self-attention along different dime…

cs.CV2023

Hierarchical Integration Diffusion Model for Realistic Image Deblurring

Zheng Chen, Yulun Zhang, Ding Liu +4

Diffusion models (DMs) have recently been introduced in image deblurring and exhibited promising performance, particularly in terms of details reconstruction. However, the diffusio…

cs.CV2023

Xformer: Hybrid X-Shaped Transformer for Image Denoising

Jiale Zhang, Yulun Zhang, Jinjin Gu +3

In this paper, we present a hybrid X-shaped vision Transformer, named Xformer, which performs notably on image denoising tasks. We explore strengthening the global representation o…

cs.CV2023

Recursive Generalization Transformer for Image Super-Resolution

Zheng Chen, Yulun Zhang, Jinjin Gu +2

Transformer architectures have exhibited remarkable performance in image super-resolution (SR). Since the quadratic computational complexity of the self-attention (SA) in Transform…

cs.CV201913 cited

TGAN: Deep Tensor Generative Adversarial Nets for Large Image Generation

Zihan Ding, Xiao-Yang Liu, Miao Yin +1

Deep generative models have been successfully applied to many applications. However, existing works experience limitations when generating large images (the literature usually gene…