activity
20242026
most citedInfrared Small Target Detection with Scale and Location Sensitivity

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Reference-based Category Discovery: Unsupervised Object Detection with Category Awareness

Yichen Li, Qiankun Liu, Ying Fu

Traditional one-shot detection methods have addressed the closed-set problem in object detection, but the high cost of data annotation remains a critical challenge. General unsuper…

cs.CV2025

MAFE R-CNN: Selecting More Samples to Learn Category-aware Features for Small Object Detection

Yichen Li, Qiankun Liu, Zhenchao Jin +3

Small object detection in intricate environments has consistently represented a major challenge in the field of object detection. In this paper, we identify that this difficulty st…

cs.CV2024

Multi-Object Tracking in the Dark

Xinzhe Wang, Kang Ma, Qiankun Liu +2

Low-light scenes are prevalent in real-world applications (e.g. autonomous driving and surveillance at night). Recently, multi-object tracking in various practical use cases have r…

cs.CV2024

Transformer based Pluralistic Image Completion with Reduced Information Loss

Qiankun Liu, Yuqi Jiang, Zhentao Tan +5

Transformer based methods have achieved great success in image inpainting recently. However, we find that these solutions regard each pixel as a token, thus suffering from an infor…

cs.CV20242 cited

Infrared Small Target Detection with Scale and Location Sensitivity

Qiankun Liu, Rui Liu, Bolun Zheng +2

Recently, infrared small target detection (IRSTD) has been dominated by deep-learning-based methods. However, these methods mainly focus on the design of complex model structures t…