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 …

We present a novel transformer-based architecture for global multi-object tracking. Our
network takes a short sequence of frames as input and produces global trajectories for all …

Optical flow is an indispensable building block for various important computer vision tasks,
including motion estimation, object tracking, and disparity measurement. In this work, we …

Drones, or general UAVs, equipped with cameras have been fast deployed with a wide
range of applications, including agriculture, aerial photography, and surveillance …

Video objection detection is a challenging task because isolated video frames may
encounter appearance deterioration, which introduces great confusion for detection. One of …

The non-local block is a popular module for strengthening the context modeling ability of a
regular convolutional neural network. This paper first studies the non-local block in depth …

Active speaker detection (ASD) seeks to detect who is speaking in a visual scene of one or
more speakers. The successful ASD depends on accurate interpretation of short-term and …

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 …

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