Existing convolutional neural network (CNN)-based and vision Transformer (ViT)-based
image restoration methods are usually explored in the spatial domain. However, we employ …

Visual tracking is the widely emerging research in computer vision applications. Nowadays,
researchers have proposed various novel tracking methodologies to attain the excellence in …

In active object tracking, given a visual observation as input, the goal is to lockup the target
by autonomously adjusting camera's position and posture. Previous works on active tracking …

Removing raindrops adhering to lenses or glass is challenging since raindrops have more
complex internal structures and optical effects than rain streaks. Existing raindrop removal …

Object tracking has always been an interesting and essential research topic in the domain of
computer vision, of which the model update mechanism is an essential work, therefore the …

With the rapid development of intelligent transportation, automated traffic surveillance is
considered as an important component. In the field of traffic surveillance, it is particularly …

Correlation filters (CF), a popular tool for visual tracking, suffer from unwanted boundary
effects due to the periodic assumption needed for FFT implementation. To address this …

Natural language tracking aims to localize the target object referred to by a language
description using a sequence of bounding boxes in video frames. Compared with traditional …

Multiple Object Tracking (MOT) focuses on tracking all the objects in a video. Most MOT
solutions follow a tracking-by-detection or a joint detection tracking paradigm to generate the …

In the field of correlation filter object tracking, the traditional template-update method easily
causes template drift, so it performs poorly in complex scenes. To enhance the robustness of …