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Artificial intelligence in the creative industries: a review
This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …
applications in the context of the creative industries. A brief background of AI, and …
Video event restoration based on keyframes for video anomaly detection
Video anomaly detection (VAD) is a significant computer vision problem. Existing deep
neural network (DNN) based VAD methods mostly follow the route of frame reconstruction or …
neural network (DNN) based VAD methods mostly follow the route of frame reconstruction or …
Deep image deblurring: A survey
Image deblurring is a classic problem in low-level computer vision with the aim to recover a
sharp image from a blurred input image. Advances in deep learning have led to significant …
sharp image from a blurred input image. Advances in deep learning have led to significant …
Deblur-nerf: Neural radiance fields from blurry images
Abstract Neural Radiance Field (NeRF) has gained considerable attention recently for 3D
scene reconstruction and novel view synthesis due to its remarkable synthesis quality …
scene reconstruction and novel view synthesis due to its remarkable synthesis quality …
Low-light image and video enhancement using deep learning: A survey
Low-light image enhancement (LLIE) aims at improving the perception or interpretability of
an image captured in an environment with poor illumination. Recent advances in this area …
an image captured in an environment with poor illumination. Recent advances in this area …
Dynamic neural networks: A survey
Dynamic neural network is an emerging research topic in deep learning. Compared to static
models which have fixed computational graphs and parameters at the inference stage …
models which have fixed computational graphs and parameters at the inference stage …
Ntire 2019 challenge on video deblurring and super-resolution: Dataset and study
This paper introduces a novel large dataset for video deblurring, video super-resolution and
studies the state-of-the-art as emerged from the NTIRE 2019 video restoration challenges …
studies the state-of-the-art as emerged from the NTIRE 2019 video restoration challenges …
Scale-recurrent network for deep image deblurring
In single image deblurring, the``coarse-to-fine''scheme, ie gradually restoring the sharp
image on different resolutions in a pyramid, is very successful in both traditional optimization …
image on different resolutions in a pyramid, is very successful in both traditional optimization …
Frame-recurrent video super-resolution
Recent advances in video super-resolution have shown that convolutional neural networks
combined with motion compensation are able to merge information from multiple low …
combined with motion compensation are able to merge information from multiple low …
Neural blind deconvolution using deep priors
Blind deconvolution is a classical yet challenging low-level vision problem with many real-
world applications. Traditional maximum a posterior (MAP) based methods rely heavily on …
world applications. Traditional maximum a posterior (MAP) based methods rely heavily on …