Related papers: Label Assignment Distillation for Object Detection
This paper has been withdrawn due to conflicts with journal copyright issues.
Recent advancements in camera-based 3D object detection have introduced cross-modal knowledge distillation to bridge the performance gap with LiDAR 3D detectors, leveraging the precise geometric information in LiDAR point clouds. However,…
This paper has been withdrawn by the author due to an extended and largely modified version of the paper was published in arXiv (see arXiv:0807.3694, Disjoint minimal graphs).
This paper has been retracted.
Knowledge distillation is a widely adopted technique for model lightening. However, the performance of most knowledge distillation methods in the domain of object detection is not satisfactory. Typically, knowledge distillation approaches…
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The author has recognized an error in the section of the text regarding induced Compton scattering. The paper has been withdrawn pending a revision to this section.
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This paper was withdrawn by arXiv admin due to authors' misrepresentation of identity/affiliation.
AutoAugment has been a powerful algorithm that improves the accuracy of many vision tasks, yet it is sensitive to the operator space as well as hyper-parameters, and an improper setting may degenerate network optimization. This paper delves…
This paper has been withdrawn by the author because overcame by arXiv:0910.4694
This paper has been withdrawn because the content has been substantially improved in a later paper, arXiv:0806.1165.
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This article was withdrawn by the arXiv.org administrators since it plagiarizes math.GT/0011056.
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This paper has been withdrawn by the author due to text overlap with arXiv:1102.5004, as well as omission of proper citations to arXiv:1110.4655 and arXiv:1111.0313