output
20162024
most citedUnitBox: An Advanced Object Detection Network

1.6k citations

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21 papers · 1 filter

cs.CV20248 cited

Class Balance Matters to Active Class-Incremental Learning

Zitong Huang, Ze Chen, Yuanze Li +6

Few-Shot Class-Incremental Learning has shown remarkable efficacy in efficient learning new concepts with limited annotations. Nevertheless, the heuristic few-shot annotations may…

cs.CV202319 cited

Label-guided Attention Distillation for Lane Segmentation

Zhikang Liu, Lanyun Zhu

Contemporary segmentation methods are usually based on deep fully convolutional networks (FCNs). However, the layer-by-layer convolutions with a growing receptive field is not good…

cs.CV202234 cited

Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise Modeling

Hansen Feng, Lizhi Wang, Yuzhi Wang +1

Low-light raw denoising is an important and valuable task in computational photography where learning-based methods trained with paired real data are mainstream. However, the limit…

cs.CV20217 cited

SiamPolar: Semi-supervised Realtime Video Object Segmentation with Polar Representation

Yaochen Li, Yuhui Hong, Yonghong Song +3

Video object segmentation (VOS) is an essential part of autonomous vehicle navigation. The real-time speed is very important for the autonomous vehicle algorithms along with the ac…

cs.CV20211 cited

Temporal Knowledge Consistency for Unsupervised Visual Representation Learning

Weixin Feng, Yuanjiang Wang, Lihua Ma +2

The instance discrimination paradigm has become dominant in unsupervised learning. It always adopts a teacher-student framework, in which the teacher provides embedded knowledge as…

cs.CV20201 cited

TP-LSD: Tri-Points Based Line Segment Detector

Siyu Huang, Fangbo Qin, Pengfei Xiong +3

This paper proposes a novel deep convolutional model, Tri-Points Based Line Segment Detector (TP-LSD), to detect line segments in an image at real-time speed. The previous related…