17 citations · 48 across the 12 of their papers we have counts for
7 papers · 1 filter
Spatial-Frequency U-Net for Denoising Diffusion Probabilistic Models
Xin Yuan, Linjie Li, Jianfeng Wang +4
In this paper, we study the denoising diffusion probabilistic model (DDPM) in wavelet space, instead of pixel space, for visual synthesis. Considering the wavelet transform represe…
Unfolding Framework with Prior of Convolution-Transformer Mixture and Uncertainty Estimation for Video Snapshot Compressive Imaging
Siming Zheng, Xin Yuan
We consider the problem of video snapshot compressive imaging (SCI), where sequential high-speed frames are modulated by different masks and captured by a single measurement. The u…
Cooperative Hardware-Prompt Learning for Snapshot Compressive Imaging
Jiamian Wang, Zongliang Wu, Yulun Zhang +3
Existing reconstruction models in snapshot compressive imaging systems (SCI) are trained with a single well-calibrated hardware instance, making their performance vulnerable to har…
EfficientSCI: Densely Connected Network with Space-time Factorization for Large-scale Video Snapshot Compressive Imaging
Lishun Wang, Miao Cao, Xin Yuan
Video snapshot compressive imaging (SCI) uses a two-dimensional detector to capture consecutive video frames during a single exposure time. Following this, an efficient reconstruct…
Text-to-Image Generation via Implicit Visual Guidance and Hypernetwork
Xin Yuan, Zhe Lin, Jason Kuen +2
We develop an approach for text-to-image generation that embraces additional retrieval images, driven by a combination of implicit visual guidance loss and generative objectives. U…
Motion-aware Dynamic Graph Neural Network for Video Compressive Sensing
Ruiying Lu, Ziheng Cheng, Bo Chen +1
Video snapshot compressive imaging (SCI) utilizes a 2D detector to capture sequential video frames and compress them into a single measurement. Various reconstruction methods have…
Multimodal Contrastive Training for Visual Representation Learning
Xin Yuan, Zhe Lin, Jason Kuen +5
We develop an approach to learning visual representations that embraces multimodal data, driven by a combination of intra- and inter-modal similarity preservation objectives. Unlik…