Related papers: Label Assignment Distillation for Object Detection

This paper has been withdrawn by the author due to an error in the proof.

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In this paper, we propose the LiDAR Distillation to bridge the domain gap induced by different LiDAR beams for 3D object detection. In many real-world applications, the LiDAR points used by mass-produced robots and vehicles usually have…

Efficient object detection methods have recently received great attention in remote sensing. Although deep convolutional networks often have excellent detection accuracy, their deployment on resource-limited edge devices is difficult.…

arXiv admin note: This submission has been removed by arXiv administrators due to unprofessional personal attack.

Training models continually to detect and classify objects, from new classes and new domains, remains an open problem. In this work, we conduct a thorough analysis of why and how object detection models forget catastrophically. We focus on…

The development of computer vision solutions for gigapixel images in digital pathology is hampered by significant computational limitations due to the large size of whole slide images. In particular, digitizing biopsies at high resolutions…

This paper has been withdrawn, as it has been merged into arXiv:1009.6144

This paper has been withdrawn, because it is subsumed by the new preprint arXiv:0806.4540 .

This paper has been withdrawn by the authors, due a crucial error in Sec. 3.

This preprint has been withdrawn. It is because I will never publish this preprint since everything has been contained in my new preprint: arXiv:0907.1506. Please refer to arXiv:0907.1506. Please do not cite this preprint any more.

This paper has been withdrawn.

Knowledge distillation is a widely used paradigm for inheriting information from a complicated teacher network to a compact student network and maintaining the strong performance. Different from image classification, object detectors are…

This paper has been withdrawn

This paper has been withdrawn by the authors due to a major rewriting.

This paper has been withdrawn by the author due to rewritting and skipping crucial sign errors.

Withdrawn by arXiv administration because authors have forged affiliations and acknowledgements, and have not adequately responded to charges [hep-th/9912039] of unattributed use of verbatim material.

This paper has been withdrawn by the author(s) in the light of several other works available and due to a misunderstanding in the authorships.

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