120 citations · 232 across the 9 of their papers we have counts for
6 papers · 1 filter
Modality-Agnostic Prompt Learning for Multi-Modal Camouflaged Object Detection
Hao Wang, Jiqing Zhang, Xin Yang +4
Camouflaged Object Detection (COD) aims to segment objects that blend seamlessly into complex backgrounds, with growing interest in exploiting additional visual modalities to enhan…
Distractor-aware Event-based Tracking
Yingkai Fu, Meng Li, Wenxi Liu +5
Event cameras, or dynamic vision sensors, have recently achieved success from fundamental vision tasks to high-level vision researches. Due to its ability to asynchronously capture…
Frame-Event Alignment and Fusion Network for High Frame Rate Tracking
Jiqing Zhang, Yuanchen Wang, Wenxi Liu +4
Most existing RGB-based trackers target low frame rate benchmarks of around 30 frames per second. This setting restricts the tracker's functionality in the real world, especially f…
Object Tracking by Jointly Exploiting Frame and Event Domain
Jiqing Zhang, Xin Yang, Yingkai Fu +3
Inspired by the complementarity between conventional frame-based and bio-inspired event-based cameras, we propose a multi-modal based approach to fuse visual cues from the frame- a…
Multi-domain Collaborative Feature Representation for Robust Visual Object Tracking
Jiqing Zhang, Kai Zhao, Bo Dong +4
Jointly exploiting multiple different yet complementary domain information has been proven to be an effective way to perform robust object tracking. This paper focuses on effective…
DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution with Large Factors
Xin Yang, Haiyang Mei, Jiqing Zhang +4
Recently, single-image super-resolution has made great progress owing to the development of deep convolutional neural networks (CNNs). The vast majority of CNN-based models use a p…