In recent years, neural image compression (NIC) algorithms have shown
po...
The previous deep video compression approaches only use the single scale...
Recently, more and more images are compressed and sent to the back-end
d...
Most video understanding methods are learned on high-quality videos. How...
Bicubic downscaling is a prevalent technique used to reduce the video st...
Efficiently modeling spatial-temporal information in videos is crucial f...
In this paper, we propose a new deep image compression framework called
...
Learning based video compression attracts increasing attention in the pa...
In this paper, we propose a two-stage deep learning framework called
Vox...
Being a crucial task of autonomous driving, Stereo matching has made gre...
In the learning based video compression approaches, it is an essential i...
Existing anchor-based and anchor-free object detectors in multi-stage or...
Existing anchor-based and anchor-free object detectors in multi-stage or...
Recently, learning based video compression methods attract increasing
at...
Image compression is a widely used technique to reduce the spatial redun...
Reconstructing 3D human shape and pose from a monocular image is challen...
Conventional video compression approaches use the predictive coding
arch...