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Sketch-R2CNN: An Attentive Network for Vector Sketch Recognition
[article]
2018
arXiv
pre-print
Sketch-R2CNN takes as input only a vector sketch with grouped sequences of points, and uses an RNN for stroke attention estimation in the vector space and a CNN for 2D feature extraction in the pixel space ...
In this paper, we propose a novel single-branch attentive network architecture RNN-Rasterization-CNN (Sketch-R2CNN for short) to fully leverage the dynamics in sketches for recognition. ...
(Sketch-R2CNN for short), for vector sketch recognition. ...
arXiv:1811.08170v1
fatcat:cwpbhbbg2zggvczwb6brw3qney
SceneTrilogy: On Scene Sketches and its Relationship with Text and Photo
[article]
2022
arXiv
pre-print
We for the first time extend multi-modal scene understanding to include that of free-hand scene sketches. ...
We spell out a few insights on the complementarity of each modality for scene understanding, and study for the first time a series of scene-specific applications like joint sketch- and text-based image ...
.: Sketch-r2cnn: An attentive network for vector sketch recognition. arXiv preprint arXiv:1811.08170 (2018) 43. ...
arXiv:2204.11964v1
fatcat:r7gaglcvqrhsni6cxqjieppfoy
CNN Variants for Computer Vision: History, Architecture, Application, Challenges and Future Scope
2021
Electronics
Deep CNN (convolution neural network) has benefited the computer vision community by producing excellent results in video processing, object recognition, picture classification and segmentation, natural ...
language processing, speech recognition, and many other fields. ...
Acknowledgments: The authors would like to thank the reviewers for their valuable suggestions which helped in improving the quality of this paper. ...
doi:10.3390/electronics10202470
fatcat:aqhrysjtbjagzl6byalgy2du5a