1 citations · 1 across the 10 of their papers we have counts for
11 papers
ATD: Improved Transformer with Adaptive Token Dictionary for Image Restoration
Leheng Zhang, Wei Long, Yawei Li +3
Recently, Transformers have gained significant popularity in image restoration tasks such as image super-resolution and denoising, owing to their superior performance. However, bal…
Task-Aware Image Signal Processor for Advanced Visual Perception
Kai Chen, Jin Xiao, Leheng Zhang +2
In recent years, there has been a growing trend in computer vision towards exploiting RAW sensor data, which preserves richer information compared to conventional low-bit RGB image…
Generative Image Compression by Estimating Gradients of the Rate-variable Feature Distribution
Minghao Han, Weiyi You, Jinhua Zhang +3
While learned image compression (LIC) focuses on efficient data transmission, generative image compression (GIC) extends this framework by integrating generative modeling to produc…
Learned Image Compression with Dictionary-based Entropy Model
Jingbo Lu, Leheng Zhang, Xingyu Zhou +3
Learned image compression methods have attracted great research interest and exhibited superior rate-distortion performance to the best classical image compression standards of the…
Neural Stereo Video Compression with Hybrid Disparity Compensation
Shiyin Jiang, Zhenghao Chen, Minghao Han +1
Disparity compensation represents the primary strategy in stereo video compression (SVC) for exploiting cross-view redundancy. These mechanisms can be broadly categorized into two…
Progressive Focused Transformer for Single Image Super-Resolution
Wei Long, Xingyu Zhou, Leheng Zhang +1
Transformer-based methods have achieved remarkable results in image super-resolution tasks because they can capture non-local dependencies in low-quality input images. However, thi…
Uncertainty-guided Perturbation for Image Super-Resolution Diffusion Model
Leheng Zhang, Weiyi You, Kexuan Shi +1
Diffusion-based image super-resolution methods have demonstrated significant advantages over GAN-based approaches, particularly in terms of perceptual quality. Building upon a leng…
Consistency Trajectory Matching for One-Step Generative Super-Resolution
Weiyi You, Mingyang Zhang, Leheng Zhang +3
Current diffusion-based super-resolution (SR) approaches achieve commendable performance at the cost of high inference overhead. Therefore, distillation techniques are utilized to…
Inductive Gradient Adjustment For Spectral Bias In Implicit Neural Representations
Kexuan Shi, Hai Chen, Leheng Zhang +1
Implicit Neural Representations (INRs), as a versatile representation paradigm, have achieved success in various computer vision tasks. Due to the spectral bias of the vanilla mult…
Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary
Leheng Zhang, Yawei Li, Xingyu Zhou +2
Single Image Super-Resolution is a classic computer vision problem that involves estimating high-resolution (HR) images from low-resolution (LR) ones. Although deep neural networks…
Video Super-Resolution Transformer with Masked Inter&Intra-Frame Attention
Xingyu Zhou, Leheng Zhang, Xiaorui Zhao +3
Recently, Vision Transformer has achieved great success in recovering missing details in low-resolution sequences, i.e., the video super-resolution (VSR) task. Despite its superior…