11 citations · 14 across the 6 of their papers we have counts for
6 papers · 1 filter
Codebook-Based Adaptive Feature Compression With Semantic Enhancement for Edge-Cloud Systems
Xinyu Wang, Zikun Zhou, Yingjian Li +2
Coding images for machines with minimal bitrate and strong analysis performance is key to effective edge-cloud systems. Several approaches deploy an image codec and perform analysi…
Channel and Spatial Relation-Propagation Network for RGB-Thermal Semantic Segmentation
Zikun Zhou, Shukun Wu, Guoqing Zhu +2
RGB-Thermal (RGB-T) semantic segmentation has shown great potential in handling low-light conditions where RGB-based segmentation is hindered by poor RGB imaging quality. The key t…
Reliability-Hierarchical Memory Network for Scribble-Supervised Video Object Segmentation
Zikun Zhou, Kaige Mao, Wenjie Pei +3
This paper aims to solve the video object segmentation (VOS) task in a scribble-supervised manner, in which VOS models are not only trained by the sparse scribble annotations but a…
Global Tracking via Ensemble of Local Trackers
Zikun Zhou, Jianqiu Chen, Wenjie Pei +3
The crux of long-term tracking lies in the difficulty of tracking the target with discontinuous moving caused by out-of-view or occlusion. Existing long-term tracking methods follo…
Saliency-Associated Object Tracking
Zikun Zhou, Wenjie Pei, Xin Li +3
Most existing trackers based on deep learning perform tracking in a holistic strategy, which aims to learn deep representations of the whole target for localizing the target. It is…
Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking
Qiao Liu, Xin Li, Zhenyu He +3
Existing deep Thermal InfraRed (TIR) trackers only use semantic features to describe the TIR object, which lack the sufficient discriminative capacity for handling distractors. Thi…