activity
20202022
most citedSG-Net: Spatial Granularity Network for One-Stage Video Instance Segmentation

13 citations · 26 across the 6 of their papers we have counts for

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7 papers · 1 filter

cs.CV20221 cited

DFA: Dynamic Feature Aggregation for Efficient Video Object Detection

Yiming Cui

Video object detection is a fundamental yet challenging task in computer vision. One practical solution is to take advantage of temporal information from the video and apply featur…

cs.CV20212 cited

DG-Labeler and DGL-MOTS Dataset: Boost the Autonomous Driving Perception

Yiming Cui, Zhiwen Cao, Yixin Xie +5

Multi-object tracking and segmentation (MOTS) is a critical task for autonomous driving applications. The existing MOTS studies face two critical challenges: 1) the published datas…

cs.CV20214 cited

TF-Blender: Temporal Feature Blender for Video Object Detection

Yiming Cui, Liqi Yan, Zhiwen Cao +1

Video objection detection is a challenging task because isolated video frames may encounter appearance deterioration, which introduces great confusion for detection. One of the pop…

cs.CV202113 cited

SG-Net: Spatial Granularity Network for One-Stage Video Instance Segmentation

Dongfang Liu, Yiming Cui, Wenbo Tan +1

Video instance segmentation (VIS) is a new and critical task in computer vision. To date, top-performing VIS methods extend the two-stage Mask R-CNN by adding a tracking branch, le…

cs.CV20211 cited

Hierarchical Attention Fusion for Geo-Localization

Liqi Yan, Yiming Cui, Yingjie Chen +1

Geo-localization is a critical task in computer vision. In this work, we cast the geo-localization as a 2D image retrieval task. Current state-of-the-art methods for 2D geo-localiz…

cs.CV20205 cited

DenserNet: Weakly Supervised Visual Localization Using Multi-scale Feature Aggregation

Dongfang Liu, Yiming Cui, Liqi Yan +3

In this work, we introduce a Denser Feature Network (DenserNet) for visual localization. Our work provides three principal contributions. First, we develop a convolutional neural n…