DNNs are becoming less and less over-parametrised due to recent advances in efficient
model design, through careful hand-crafted or NAS-based methods. Relying on the fact that …

BiSeNet has been proved to be a popular two-stream network for real-time segmentation.
However, its principle of adding an extra path to encode spatial information is time …

Two-branch network architecture has shown its efficiency and effectiveness in real-time
semantic segmentation tasks. However, direct fusion of high-resolution details and low …

We present a novel, real-time, semantic segmentation network in which the encoder both
encodes and generates the parameters (weights) of the decoder. Furthermore, to allow …

As one of the fundamental technologies for scene understanding, semantic segmentation
has been widely explored in the last few years. Light field cameras encode the geometric …

Video segmentation—partitioning video frames into multiple segments or objects—plays a
critical role in a broad range of practical applications, from enhancing visual effects in movie …

This paper presents Video K-Net, a simple, strong, and unified framework for fully end-to-
end video panoptic segmentation. The method is built upon K-Net, a method that unifies …

In this paper, we present a new large-scale dataset for the video panoptic segmentation
task, which aims to assign semantic classes and track identities to all pixels in a video. As …

Multi-task learning is an open and challenging problem in computer vision. The typical way
of conducting multi-task learning with deep neural networks is either through handcrafted …

We present a systematic study on a new task called dichotomous image segmentation (DIS),
which aims to segment highly accurate objects from natural images. To this end, we …