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Found 7 papers, 0 papers with code
A Structured Pruning Algorithm for Model-based Deep Learning
There is a growing interest in model-based deep learning (MBDL) for solving imaging inverse problems.
A Plug-and-Play Image Registration Network
A traditional DL approach to DIR is based on training a convolutional neural network (CNN) to estimate the registration field between two input images.
Robustness of Deep Equilibrium Architectures to Changes in the Measurement Model
Deep model-based architectures (DMBAs) are widely used in imaging inverse problems to integrate physical measurement models and learned image priors.
SINCO: A Novel structural regularizer for image compression using implicit neural representations
Implicit neural representations (INR) have been recently proposed as deep learning (DL) based solutions for image compression.
Visual-aware Attention Dual-stream Decoder for Video Captioning
Video captioning is a challenging task that captures different visual parts and describes them in sentences, for it requires visual and linguistic coherence.
VERAM: View-Enhanced Recurrent Attention Model for 3D Shape Classification
Multi-view deep neural network is perhaps the most successful approach in 3D shape classification.
Tracking Deformable Parts via Dynamic Conditional Random Fields
Despite the success of many advanced tracking methods in this area, tracking targets with drastic variation of appearance such as deformation, view change and partial occlusion in video sequences is still a challenge in practical applications.
