Papers Rolling Shutter Correction
“Rolling Shutter Correction” 태그가 달린 논문 216편 · 필터 해제
StableMotion: Repurposing Diffusion-Based Image Priors for Motion Estimation
We present StableMotion, a novel framework leverages knowledge (geometry and content priors) from pretrained large-scale image diffusion models to perform motion estimation, solving single-image-based image rectification…
Motion EstimationRolling Shutter CorrectionSelfDRSC++: Self-Supervised Learning for Dual Reversed Rolling Shutter Correction
Modern consumer cameras commonly employ the rolling shutter (RS) imaging mechanism, via which images are captured by scanning scenes row-by-row, resulting in RS distortion for dynamic scenes. To correct RS distortion, ex…
distortion correctionRolling Shutter CorrectionSelf-Supervised LearningVideo Frame InterpolationRolling Shutter Correction with Intermediate Distortion Flow Estimation
This paper proposes to correct the rolling shutter (RS) distorted images by estimating the distortion flow from the global shutter (GS) to RS directly. Existing methods usually perform correction using the undistortion f…
Rolling Shutter CorrectionEVS-assisted Joint Deblurring Rolling-Shutter Correction and Video Frame Interpolation through Sensor Inverse Modeling
Event-based Vision Sensors (EVS) gain popularity in enhancing CMOS Image Sensor (CIS) video capture. Nonidealities of EVS such as pixel or readout latency can significantly influence the quality of the enhanced image…
DeblurringEvent-based visionRolling Shutter CorrectionVideo Frame InterpolationStochastic Unrolled Federated Learning
Algorithm unrolling has emerged as a learning-based optimization paradigm that unfolds truncated iterative algorithms in trainable neural-network optimizers. We introduce Stochastic UnRolled Federated learning (SURF), a …
Federated LearningGraph Neural NetworkRolling Shutter CorrectionUniINR: Event-guided Unified Rolling Shutter Correction, Deblurring, and Interpolation
Video frames captured by rolling shutter (RS) cameras during fast camera movement frequently exhibit RS distortion and blur simultaneously. Naturally, recovering high-frame-rate global shutter (GS) sharp frames from an R…
DeblurringImage RestorationRolling Shutter CorrectionNeural Image Re-Exposure
The shutter strategy applied to the photo-shooting process has a significant influence on the quality of the captured photograph. An improper shutter may lead to a blurry image, video discontinuity, or rolling shutter ar…
DeblurringDecoderJoint Deblur and Frame InterpolationJoint Deblur and Unrolling+4Basis Pursuit Denoising via Recurrent Neural Network Applied to Super-resolving SAR Tomography
Finding sparse solutions of underdetermined linear systems commonly requires the solving of L1 regularized least squares minimization problem, which is also known as the basis pursuit denoising (BPDN). They are computati…
Computational EfficiencyDenoisingDescriptiveRolling Shutter Correction+1A Compound Gaussian Least Squares Algorithm and Unrolled Network for Linear Inverse Problems
For solving linear inverse problems, particularly of the type that appears in tomographic imaging and compressive sensing, this paper develops two new approaches. The first approach is an iterative algorithm that minimiz…
Compressive SensingImage ReconstructionRolling Shutter CorrectionImproving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback
We study whether multiple large language models (LLMs) can autonomously improve each other in a negotiation game by playing, reflecting, and criticizing. We are interested in this question because if LLMs were able to im…
In-Context LearningLanguage ModelingLanguage ModellingRolling Shutter CorrectionTowards Nonlinear-Motion-Aware and Occlusion-Robust Rolling Shutter Correction
This paper addresses the problem of rolling shutter correction in complex nonlinear and dynamic scenes with extreme occlusion. Existing methods suffer from two main drawbacks. Firstly, they face challenges in estimating …
Rolling Shutter CorrectionSMUG: Towards robust MRI reconstruction by smoothed unrolling
Although deep learning (DL) has gained much popularity for accelerated magnetic resonance imaging (MRI), recent studies have shown that DL-based MRI reconstruction models could be oversensitive to tiny input perturbation…
Adversarial Defenseimage-classificationImage ClassificationImage Reconstruction+2A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection in OFDM Systems
Joint channel estimation and signal detection (JCESD) is crucial in orthogonal frequency division multiplexing (OFDM) systems, but traditional algorithms perform poorly in low signal-to-noise ratio (SNR) scenarios. Deep …
Rolling Shutter CorrectionHyperspectral Compressive Wavefront Sensing
Presented is a novel way to combine snapshot compressive imaging and lateral shearing interferometry in order to capture the spatio-spectral phase of an ultrashort laser pulse in a single shot. A deep unrolling algorithm…
compressed sensingRolling Shutter CorrectionClosed-Loop Transcription via Convolutional Sparse Coding
Autoencoding has achieved great empirical success as a framework for learning generative models for natural images. Autoencoders often use generic deep networks as the encoder or decoder, which are difficult to interpret…
Rolling Shutter CorrectionHubbard-Stratonovich Detector for Simple Trainable MIMO Signal Detection
Massive multiple-input multiple-output (MIMO) is a key technology used in fifth-generation wireless communication networks and beyond. Recently, various MIMO signal detectors based on deep learning have been proposed. Es…
Rolling Shutter CorrectionTowards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration
The great success of Deep Neural Networks (DNNs) has inspired the algorithmic development of DNN-based Fixed-Point (DNN-FP) for computer vision tasks. DNN-FP methods, trained by Back-Propagation Through Time or computing…
Image RestorationRolling Shutter CorrectionBackpropagation of Unrolled Solvers with Folded Optimization
The integration of constrained optimization models as components in deep networks has led to promising advances on many specialized learning tasks. A central challenge in this setting is backpropagation through the solut…
Rolling Shutter CorrectionStructured PredictionReachability Analysis of Neural Network Control Systems
Neural network controllers (NNCs) have shown great promise in autonomous and cyber-physical systems. Despite the various verification approaches for neural networks, the safety analysis of NNCs remains an open problem. E…
Rolling Shutter CorrectionTraining End-to-End Unrolled Iterative Neural Networks for SPECT Image Reconstruction
Training end-to-end unrolled iterative neural networks for SPECT image reconstruction requires a memory-efficient forward-backward projector for efficient backpropagation. This paper describes an open-source, high perfor…
Image ReconstructionRolling Shutter Correction