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Found 7 papers, 3 papers with code
MOSE: Boosting Vision-based Roadside 3D Object Detection with Scene Cues
3D object detection based on roadside cameras is an additional way for autonomous driving to alleviate the challenges of occlusion and short perception range from vehicle cameras.
Distilling Object Detectors With Global Knowledge
Then, a robust distilling module (RDM) is applied to construct the global knowledge based on the prototypes and filtrate noisy global and local knowledge by measuring the discrepancy of the representations in two feature spaces.
Rethinking Pseudo-labeled Sample Mining for Semi-Supervised Object Detection
However, the impact of the pseudo-labeled samples' quality as well as the mining strategies for high quality training sample have rarely been studied in SSL.
Learning a Domain Classifier Bank for Unsupervised Adaptive Object Detection
To tackle this issue, we develop a fine-grained domain alignment approach with a well-designed domain classifier bank that achieves the instance-level alignment respecting to their categories.
Text Perceptron: Towards End-to-End Arbitrary-Shaped Text Spotting
Many approaches have recently been proposed to detect irregular scene text and achieved promising results.
Ranked #8 on
Text Spotting
on SCUT-CTW1500
Online PCB Defect Detector On A New PCB Defect Dataset
To train the deep model, a dataset is established, namely DeepPCB, which contains 1, 500 image pairs with annotations including positions of 6 common types of PCB defects.
Adversarial Attack Type I: Cheat Classifiers by Significant Changes
Despite the great success of deep neural networks, the adversarial attack can cheat some well-trained classifiers by small permutations.
