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Image super-resolution: A comprehensive review, recent trends, challenges and applications
Super resolution (SR) is an eminent system in the field of computer vison and image
processing to improve the visual perception of the poor-quality images. The key objective of …
processing to improve the visual perception of the poor-quality images. The key objective of …
Video super-resolution based on deep learning: a comprehensive survey
Video super-resolution (VSR) is reconstructing high-resolution videos from low resolution
ones. Recently, the VSR methods based on deep neural networks have made great …
ones. Recently, the VSR methods based on deep neural networks have made great …
The cell tracking challenge: 10 years of objective benchmarking
Abstract The Cell Tracking Challenge is an ongoing benchmarking initiative that has
become a reference in cell segmentation and tracking algorithm development. Here, we …
become a reference in cell segmentation and tracking algorithm development. Here, we …
Propainter: Improving propagation and transformer for video inpainting
Flow-based propagation and spatiotemporal Transformer are two mainstream mechanisms
in video inpainting (VI). Despite the effectiveness of these components, they still suffer from …
in video inpainting (VI). Despite the effectiveness of these components, they still suffer from …
Neural video compression with feature modulation
The emerging conditional coding-based neural video codec (NVC) shows superiority over
commonly-used residual coding-based codec and the latest NVC already claims to …
commonly-used residual coding-based codec and the latest NVC already claims to …
Flowformer: A transformer architecture for optical flow
We introduce optical Flow transFormer, dubbed as FlowFormer, a transformer-based neural
network architecture for learning optical flow. FlowFormer tokenizes the 4D cost volume built …
network architecture for learning optical flow. FlowFormer tokenizes the 4D cost volume built …
Flowformer++: Masked cost volume autoencoding for pretraining optical flow estimation
FlowFormer introduces a transformer architecture into optical flow estimation and achieves
state-of-the-art performance. The core component of FlowFormer is the transformer-based …
state-of-the-art performance. The core component of FlowFormer is the transformer-based …
Exploring video quality assessment on user generated contents from aesthetic and technical perspectives
The rapid increase in user-generated-content (UGC) videos calls for the development of
effective video quality assessment (VQA) algorithms. However, the objective of the UGC …
effective video quality assessment (VQA) algorithms. However, the objective of the UGC …
Vrt: A video restoration transformer
Video restoration aims to restore high-quality frames from low-quality frames. Different from
single image restoration, video restoration generally requires to utilize temporal information …
single image restoration, video restoration generally requires to utilize temporal information …
Recurrent video restoration transformer with guided deformable attention
Video restoration aims at restoring multiple high-quality frames from multiple low-quality
frames. Existing video restoration methods generally fall into two extreme cases, ie, they …
frames. Existing video restoration methods generally fall into two extreme cases, ie, they …