Video object detection, a basic task in the computer vision field, is rapidly evolving and
widely used. In recent years, deep learning methods have rapidly become widespread in the …

Although there are well established object detection methods based on static images, their
application to video data on a frame by frame basis faces two shortcomings:(i) lack of …

A recurrent structure is a popular framework choice for the task of video super-resolution.
The state-of-the-art method BasicVSR adopts bidirectional propagation with feature …

Video super-resolution (VSR) approaches tend to have more components than the image
counterparts as they need to exploit the additional temporal dimension. Complex designs …

How do humans recognize an object in a piece of video? Due to the deteriorated quality of
single frame, it may be hard for people to identify an occluded object in this frame by just …

Video segmentation aims to segment and track every pixel in diverse scenarios accurately.
In this paper, we present Tube-Link, a versatile framework that addresses multiple core tasks …

Detection Transformer (DETR) and Deformable DETR have been proposed to eliminate the
need for many hand-designed components in object detection while demonstrating good …

Video objection detection (VID) has been a rising research direction in recent years. A
central issue of VID is the appearance degradation of video frames caused by fast motion …

Recently, video surveillance has garnered considerable attention in various real-time
applications. Due to advances in the field of machine learning, numerous techniques have …

Adversarial examples have been demonstrated to threaten many computer vision tasks
including object detection. However, the existing attacking methods for object detection have …