Scale attentive network for scene recognition
WebIn this paper, we address the scene segmentation task by capturing rich contextual dependencies based on the self-attention mechanism. Unlike previous works that capture contexts by multi-scale features fusion, we propose a Dual Attention Networks (DANet) to adaptively integrate local features with their global dependencies. WebNov 10, 2015 · Incorporating multi-scale features in fully convolutional neural networks (FCNs) has been a key element to achieving state-of-the-art performance on semantic …
Scale attentive network for scene recognition
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WebDec 31, 2024 · Scene-Adaptive Attention Network for Crowd Counting. In recent years, significant progress has been made on the research of crowd counting. However, as the … WebHowever, Crowd counting for congested scenes often suffers from some obstacles including severe occlusions, large scale variations, noise interference, etc. In this paper, using the first ten layers of a modified VGG16 and dilated convolution layers as the framework, we have proposed a CNN based crowd counting and density estimation model …
WebThe technique for target detection based on a convolutional neural network has been widely implemented in the industry. However, the detection accuracy of X-ray images in security screening scenarios still requires improvement. This paper proposes a coupled multi-scale feature extraction and multi-scale attention architecture. We integrate this architecture … WebWe propose a network for Congested Scene Recognition called CSRNet to provide a data-driven and deep learning method that can understand highly congested scenes and perform accurate count estimation as well as present high-quality density maps. The proposed CSRNet is composed of two major components: a convolutional neural network
Webwith di erent scales in scene text recognition. We propose a novel scale aware feature encoder (SAFE) that is designed speci cally for encoding characters with di erent scales. SAFE is composed of a multi-scale con-volutional encoder and a scale attention network. The multi-scale convo- WebApr 13, 2024 · Multi-scale feature fusion techniques and covariance pooling have been shown to have positive implications for completing computer vision tasks, including fine …
WebSpecifically, the dynamic log-polar transformer learns the log-polar origin to adaptively convert the arbitrary rotations and scales of scene texts into the shifts in the log-polar space, which is helpful to generate the rotation-aware and scale-aware visual representation. Next, the sequence recognition network is an encoder-decoder model ...
WebFeb 1, 2024 · In this paper, we propose the effective parts attention network (EPAN), which automatically neglects the noisy parts and focuses on the effective parts of images, and selects some salient parts as additional assistant information for text recognition. The recognition task is divided into three steps. lace up block heel shoesWebJun 2, 2024 · Scene text recognition refers to recognizing a sequence of characters that appear in a natural image. Inspired by the success [] in neural machine translation, many of the recently proposed scene text recognizers [6, 7, 20, 21, 29] adopt an encoder-decoder framework with an attention mechanism.Despite the remarkable results reported by them, … pronunciation of louisville kyWebLong-term recurrent convolutional networks for visual recognition and description. In Proceedings of the IEEE conference on computer vision and pattern recognition, 2625–2634. Google Scholar; Feichtenhofer, C.; Pinz, A.; and Wildes, R. 2014. Bags of spacetime energies for dynamic scene recognition. lace up block heel bootiesWebApr 13, 2024 · We propose an encoder-alignment-decoder framework for scene text recognition, which consists of three components: an encoder network, a deformable attention alignment module (DAAM), and a mask transformer decoder, as shown in Fig. 2.For an input image I, the encoder network aims to extract multi-scale 2D feature maps … pronunciation of lovedWebApr 5, 2024 · Although it has achieved considerable progress in recent years, recognizing irregular text in natural scene is still a challenging problem due to the distortion and … pronunciation of lughWebScene text recognition, the final step of the scene text reading system, has made impressive progress based on deep neural networks. However, existing recognition methods devote … pronunciation of lughnasaWebScene text recognition, which detects and recognizes the text in the image, has engaged extensive research interest. Attention mechanism based methods for scene text recognition have achieved competitive performance. For scene text recognition, the attention mechanism is usually combined with RNN structures as a module to predict the results. … lace up black leggings