Coarse-to-fine deep video coding with hyperprior-guided mode prediction
The previous deep video compression approaches only use the single scale motion
compensation strategy and rarely adopt the mode prediction technique from the traditional …
compensation strategy and rarely adopt the mode prediction technique from the traditional …
Neural residual radiance fields for streamably free-viewpoint videos
The success of the Neural Radiance Fields (NeRFs) for modeling and free-view rendering
static objects has inspired numerous attempts on dynamic scenes. Current techniques that …
static objects has inspired numerous attempts on dynamic scenes. Current techniques that …
Conflict-based cross-view consistency for semi-supervised semantic segmentation
Semi-supervised semantic segmentation (SSS) has recently gained increasing research
interest as it can reduce the requirement for large-scale fully-annotated training data. The …
interest as it can reduce the requirement for large-scale fully-annotated training data. The …
Non-semantics suppressed mask learning for unsupervised video semantic compression
Most video compression methods aim to improve the decoded video visual quality, instead
of particularly guaranteeing the semantic-completeness, which deteriorates downstream …
of particularly guaranteeing the semantic-completeness, which deteriorates downstream …
Complexity-guided slimmable decoder for efficient deep video compression
In this work, we propose the complexity-guided slimmable decoder (cgSlimDecoder) in
combination with skip-adaptive entropy coding (SaEC) for efficient deep video compression …
combination with skip-adaptive entropy coding (SaEC) for efficient deep video compression …
Content adaptive latents and decoder for neural image compression
In recent years, neural image compression (NIC) algorithms have shown powerful coding
performance. However, most of them are not adaptive to the image content. Although …
performance. However, most of them are not adaptive to the image content. Although …
Neural video compression with spatio-temporal cross-covariance transformers
Although existing neural video compression~(NVC) methods have achieved significant
success, most of them focus on improving either temporal or spatial information separately …
success, most of them focus on improving either temporal or spatial information separately …
Clsa: a contrastive learning framework with selective aggregation for video rescaling
Video rescaling has recently drawn extensive attention for its practical applications such as
video compression. Compared to video super-resolution, which focuses on upscaling …
video compression. Compared to video super-resolution, which focuses on upscaling …
Improving rgb-d point cloud registration by learning multi-scale local linear transformation
Point cloud registration aims at estimating the geometric transformation between two point
cloud scans, in which point-wise correspondence estimation is the key to its success. In …
cloud scans, in which point-wise correspondence estimation is the key to its success. In …
One-click upgrade from 2D to 3D: Sandwiched RGB-D video compression for stereoscopic teleconferencing
Stereoscopic video conferencing is still challenging due to the need to compress stereo
RGB-D video in real-time. Though hardware implementations of standard video codecs such …
RGB-D video in real-time. Though hardware implementations of standard video codecs such …