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20132022
most citedWeakly Aligned Feature Fusion for Multimodal Object Detection

97 citations · 128 across the 6 of their papers we have counts for

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Showing cs.CVShow all

5 papers · 1 filter

cs.CV2022★ 1 cited

Automatically Discovering Novel Visual Categories with Self-supervised Prototype Learning

Lu Zhang, Lu Qi, Xu Yang +3

This paper tackles the problem of novel category discovery (NCD), which aims to discriminate unknown categories in large-scale image collections. The NCD task is challenging due to…

cs.CV2022★ 97 cited

Weakly Aligned Feature Fusion for Multimodal Object Detection

Lu Zhang, Zhiyong Liu, Xiangyu Zhu +4

To achieve accurate and robust object detection in the real-world scenario, various forms of images are incorporated, such as color, thermal, and depth. However, multimodal data of…

cs.CV2022

Unseen Object Instance Segmentation with Fully Test-time RGB-D Embeddings Adaptation

Lu Zhang, Siqi Zhang, Xu Yang +2

Segmenting unseen objects is a crucial ability for the robot since it may encounter new environments during the operation. Recently, a popular solution is leveraging RGB-D features…

cs.CV2019★ 25 cited

Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection

Lu Zhang, Xiangyu Zhu, Xiangyu Chen +3

Multispectral pedestrian detection has shown great advantages under poor illumination conditions, since the thermal modality provides complementary information for the color image.…

cs.CV2013★ 1 cited

GNCGCP - Graduated NonConvexity and Graduated Concavity Procedure

Zhi-Yong Liu, Hong Qiao

In this paper we propose the Graduated NonConvexity and Graduated Concavity Procedure (GNCGCP) as a general optimization framework to approximately solve the combinatorial optimiza…