Dense Object Detection

12 papers with code • 1 benchmarks • 2 datasets

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Libraries

Use these libraries to find Dense Object Detection models and implementations

Most implemented papers

Focal Loss for Dense Object Detection

facebookresearch/detectron ICCV 2017

Our novel Focal Loss focuses training on a sparse set of hard examples and prevents the vast number of easy negatives from overwhelming the detector during training.

Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection

implus/GFocal NeurIPS 2020

Specifically, we merge the quality estimation into the class prediction vector to form a joint representation of localization quality and classification, and use a vector to represent arbitrary distribution of box locations.

Precise Detection in Densely Packed Scenes

eg4000/SKU110K_CVPR19 CVPR 2019

We propose a novel, deep-learning based method for precise object detection, designed for such challenging settings.

Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection

implus/GFocalV2 CVPR 2021

Such a property makes the distribution statistics of a bounding box highly correlated to its real localization quality.

BorderDet: Border Feature for Dense Object Detection

Megvii-BaseDetection/BorderDet ECCV 2020

In this paper, We propose a simple and efficient operator called Border-Align to extract "border features" from the extreme point of the border to enhance the point feature.

Benchmark for Generic Product Detection: A Low Data Baseline for Dense Object Detection

ParallelDots/generic-sku-detection-benchmark 19 Dec 2019

We train a standard object detector on a small, normally packed dataset with data augmentation techniques.

AutoAssign: Differentiable Label Assignment for Dense Object Detection

Megvii-BaseDetection/AutoAssign 7 Jul 2020

During training, to both satisfy the prior distribution of data and adapt to category characteristics, we present Center Weighting to adjust the category-specific prior distributions.

A Solution to Product detection in Densely Packed Scenes

Media-Smart/SKU110K-DenseDet 23 Jul 2020

To grasp the essential feature of the densely packed scenes, we analysis the stages of a detector and investigate the bottleneck which limits the performance.

Robust and Efficient Post-Processing for Video Object Detection (REPP)

AlbertoSabater/Robust-and-efficient-post-processing-for-video-object-detection 1 Oct 2020

Object recognition in video is an important task for plenty of applications, including autonomous driving perception, surveillance tasks, wearable devices or IoT networks.