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Jingchun Cheng

3 accepted papers

2025

Exploring the Simplification Limit of Deep Network Features With Subway Positioning Task

RA-L 2025

This paper addresses vision-based subway positioning, a significant yet challenging task due to the low-lighting and sparse-texture conditions in tunnels. Traditional features struggle with temporal correspondence. While deep network features are effective, their computational and storage demands ma

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2018

Fast and Accurate Online Video Object Segmentation via Tracking Parts

CVPR 2018poster

Online video object segmentation is a challenging task as it entails to process the image sequence timely and accurately. To segment a target object through the video, numerous CNN-based methods have been developed by heavily finetuning on the object mask in the first frame, which is time-consuming…

2017

SegFlow: Joint Learning for Video Object Segmentation and Optical Flow

ICCV 2017poster

This paper proposes an end-to-end trainable network, SegFlow, for simultaneously predicting pixel-wise object segmentation and optical flow in videos. The proposed SegFlow has two branches where useful information of object segmentation and optical flow is propagated bidirectionally in a unified fra…

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