Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Wan, Zhaoyi"'
Publikováno v:
Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, pp. 781- 792. Feb. 6-8, 2022
In this paper, we propose SparseDet for end-to-end 3D object detection from point cloud. Existing works on 3D object detection rely on dense object candidates over all locations in a 3D or 2D grid following the mainstream methods for object detection
Externí odkaz:
http://arxiv.org/abs/2206.00960
Recently, segmentation-based scene text detection methods have drawn extensive attention in the scene text detection field, because of their superiority in detecting the text instances of arbitrary shapes and extreme aspect ratios, profiting from the
Externí odkaz:
http://arxiv.org/abs/2202.10304
In this paper, we address the problem of makeup transfer, which aims at transplanting the makeup from the reference face to the source face while preserving the identity of the source. Existing makeup transfer methods have made notable progress in ge
Externí odkaz:
http://arxiv.org/abs/2104.02894
In this paper, we are concerned with the detection of a particular type of objects with extreme aspect ratios, namely \textbf{slender objects}. In real-world scenarios, slender objects are actually very common and crucial to the objective of a detect
Externí odkaz:
http://arxiv.org/abs/2011.08529
Publikováno v:
EEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, June 2020
The pursuit of high performance on public benchmarks has been the driving force for research in scene text recognition, and notable progress has been achieved. However, a close investigation reveals a startling fact that the state-of-the-art methods
Externí odkaz:
http://arxiv.org/abs/2005.03959
Driven by deep learning and the large volume of data, scene text recognition has evolved rapidly in recent years. Formerly, RNN-attention based methods have dominated this field, but suffer from the problem of \textit{attention drift} in certain situ
Externí odkaz:
http://arxiv.org/abs/1912.12422
Recently, segmentation-based methods are quite popular in scene text detection, as the segmentation results can more accurately describe scene text of various shapes such as curve text. However, the post-processing of binarization is essential for se
Externí odkaz:
http://arxiv.org/abs/1911.08947
Scene text recognition has been an important, active research topic in computer vision for years. Previous approaches mainly consider text as 1D signals and cast scene text recognition as a sequence prediction problem, by feat of CTC or attention bas
Externí odkaz:
http://arxiv.org/abs/1907.09705
Autor:
Liao, Minghui, Zhang, Jian, Wan, Zhaoyi, Xie, Fengming, Liang, Jiajun, Lyu, Pengyuan, Yao, Cong, Bai, Xiang
Inspired by speech recognition, recent state-of-the-art algorithms mostly consider scene text recognition as a sequence prediction problem. Though achieving excellent performance, these methods usually neglect an important fact that text in images ar
Externí odkaz:
http://arxiv.org/abs/1809.06508
Akademický článek
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