17 citations · 48 across the 12 of their papers we have counts for
12 papers
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…
Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation
Xin Yuan, Pedro Savarese, Michael Maire
We develop an approach to efficiently grow neural networks, within which parameterization and optimization strategies are designed by considering their effects on the training dyna…
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…
Block Modulating Video Compression: An Ultra Low Complexity Image Compression Encoder for Resource Limited Platforms
Siming Zheng, Yujia Xue, Waleed Tahir +6
We consider the image and video compression on resource limited platforms. An ultra low-cost image encoder, named Block Modulating Video Compression (BMVC) with an encoding complex…
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…
Two-Stage is Enough: A Concise Deep Unfolding Reconstruction Network for Flexible Video Compressive Sensing
Siming Zheng, Xiaoyu Yang, Xin Yuan
We consider the reconstruction problem of video compressive sensing (VCS) under the deep unfolding/rolling structure. Yet, we aim to build a flexible and concise model using minimu…
Ensemble learning priors unfolding for scalable Snapshot Compressive Sensing
Chengshuai Yang, Shiyu Zhang, Xin Yuan
Snapshot compressive imaging (SCI) can record the 3D information by a 2D measurement and from this 2D measurement to reconstruct the original 3D information by reconstruction algor…
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…
Growing Efficient Deep Networks by Structured Continuous Sparsification
Xin Yuan, Pedro Savarese, Michael Maire
We develop an approach to growing deep network architectures over the course of training, driven by a principled combination of accuracy and sparsity objectives. Unlike existing pr…