Search Results for author: Kaige Mao

Found 3 papers, 3 papers with code

Reliability-Hierarchical Memory Network for Scribble-Supervised Video Object Segmentation

1 code implementation25 Mar 2023 Zikun Zhou, Kaige Mao, Wenjie Pei, Hongpeng Wang, YaoWei Wang, Zhenyu He

To be specific, RHMNet first only uses the memory in the high-reliability level to locate the region with high reliability belonging to the target, which is highly similar to the initial target scribble.

Semantic Segmentation Video Object Segmentation +1

Joint Visual Grounding and Tracking with Natural Language Specification

1 code implementation CVPR 2023 Li Zhou, Zikun Zhou, Kaige Mao, Zhenyu He

Such a separated framework overlooks the link between visual grounding and tracking, which is that the natural language descriptions provide global semantic cues for localizing the target for both two steps.

Visual Grounding Visual Tracking

Global Tracking via Ensemble of Local Trackers

1 code implementation CVPR 2022 Zikun Zhou, Jianqiu Chen, Wenjie Pei, Kaige Mao, Hongpeng Wang, Zhenyu He

While it can exploit the temporal context like historical appearances and locations of the target, a potential limitation of such strategy is that the local tracker tends to misidentify a nearby distractor as the target instead of activating the re-detector when the real target is out of view.

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