activity
20162023
most citedGeneralized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

272 citations · 967 across the 31 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.CV2022★ 136 cited

One-Stage Cascade Refinement Networks for Infrared Small Target Detection

Yimian Dai, Xiang Li, Fei Zhou +3

Single-frame InfraRed Small Target (SIRST) detection has been a challenging task due to a lack of inherent characteristics, imprecise bounding box regression, a scarcity of real-wo…

cs.CV2022★ 2 cited

Curriculum Temperature for Knowledge Distillation

Zheng Li, Xiang Li, Lingfeng Yang +5

Most existing distillation methods ignore the flexible role of the temperature in the loss function and fix it as a hyper-parameter that can be decided by an inefficient grid searc…

cs.CV2022★ 2 cited

DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completion

Zhiqiang Yan, Kun Wang, Xiang Li +3

Unsupervised depth completion aims to recover dense depth from the sparse one without using the ground-truth annotation. Although depth measurement obtained from LiDAR is usually s…

cs.CV2022★ 36 cited

Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality

Xiang Li, Wenhai Wang, Lingfeng Yang +1

Masked AutoEncoder (MAE) has recently led the trends of visual self-supervision area by an elegant asymmetric encoder-decoder design, which significantly optimizes both the pre-tra…

cs.CV2022★ 10 cited

RecursiveMix: Mixed Learning with History

Lingfeng Yang, Xiang Li, Borui Zhao +2

Mix-based augmentation has been proven fundamental to the generalization of deep vision models. However, current augmentations only mix samples at the current data batch during tra…

cs.CV2022★ 1 cited

Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information

Lingfeng Yang, Xiang Li, Renjie Song +5

Fine-grained image classification is a challenging computer vision task where various species share similar visual appearances, resulting in misclassification if merely based on vi…