Titlebook: Computer Vision – ACCV 2020 Workshops; 15th Asian Conferenc Imari Sato,Bohyung Han Conference proceedings 2021 Springer Nature Switzerland

晚來的提名

Spatial and Channel Attention Modulated Network for Medical Image Segmentationions via investigating relevant feature association. The proposed spatial and channel attention modules can be used in a plug and play manner and embedded after any learned feature map for adaptively emphasizing discriminant features and neglecting irrelevant information. Furthermore, we propose two

AV-node

Unsupervised Multispectral and Hyperspectral Image Fusion with Deep Spatial and Spectral Priorsolution enhancement, and impressive performance has been validated. As it is known that deep learning-based methods essentially require large-scale training samples, which are hard to obtain due to the limitation of the existing HS cameras, for constructing the model with good generalization. Motiva

重疊

G-GCSN: Global Graph Convolution Shrinkage Network for Emotion Perception from Gaitcapture the emotion-related features. We validate the effectiveness of the proposed method on a public dataset (i.e., Emotion-Gait dataset). The proposed G-GCSN achieves improvements compared with state-of-the-art methods.

征稅

Cell Detection and Segmentation in Microscopy Images with Improved Mask R-CNN detection and segmentation. The conventional Mask R-CNN employs cross entropy loss for evaluating the object detection fidelity, and equally treats all training samples in learning procedure regardless to the properties of the objects such as easily or hard degree for detection, which may lead to m

AWL

freight

Visible and Thermal Camera-Based Jaywalking Estimation Using a Hierarchical Deep Learning Framework legal or illegal crossing scenes. The proposed framework is validated on the FLIR public dataset and compared with baseline algorithms. The experimental results show that the proposed hierarchical strategy reports better accuracy than baseline algorithms in real-time.

常到

Towards Locality Similarity Preserving to 3D Human Pose Estimation during the inference. Moreover, to increase the search speed, we propose a candidate selecting mechanism to narrow the original source data. We evaluate our approach on three well-design benchmarks, including Human3.6M, HumanEva-I, and MPII. The extensive experimental results show the effectiveness

背書

Multiview Similarity Learning for Robust Visual Clusteringsome advantage in removing noise and outliers, which motivates us to introduce the data representation via low-rank constraint in order to generate clean reconstructed data for robust graph learning in each view. Secondly, a multiview scheme is established to learn the consensus similarity by dynami

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幼稚