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[HTML][HTML] Survey on videos data augmentation for deep learning models
In most Computer Vision applications, Deep Learning models achieve state-of-the-art
performances. One drawback of Deep Learning is the large amount of data needed to train …
performances. One drawback of Deep Learning is the large amount of data needed to train …
Towards discriminative representation learning for unsupervised person re-identification
In this work, we address the problem of unsupervised domain adaptation for person re-ID
where annotations are available for the source domain but not for target. Previous methods …
where annotations are available for the source domain but not for target. Previous methods …
Compression-aware video super-resolution
Videos stored on mobile devices or delivered on the Internet are usually in compressed
format and are of various unknown compression parameters, but most video super …
format and are of various unknown compression parameters, but most video super …
Delving into probabilistic uncertainty for unsupervised domain adaptive person re-identification
Clustering-based unsupervised domain adaptive (UDA) person re-identification (ReID)
reduces exhaustive annotations. However, owing to unsatisfactory feature embedding and …
reduces exhaustive annotations. However, owing to unsatisfactory feature embedding and …
Benchmarking the robustness of temporal action detection models against temporal corruptions
Temporal action detection (TAD) aims to locate action positions and recognize action
categories in long-term untrimmed videos. Although many methods have achieved …
categories in long-term untrimmed videos. Although many methods have achieved …
A feature-space multimodal data augmentation technique for text-video retrieval
Every hour, huge amounts of visual contents are posted on social media and user-
generated content platforms. To find relevant videos by means of a natural language query …
generated content platforms. To find relevant videos by means of a natural language query …
Markov game video augmentation for action segmentation
This paper addresses data augmentation for action segmentation. Our key novelty is that we
augment the original training videos in the deep feature space, not in the visual …
augment the original training videos in the deep feature space, not in the visual …
Shapeaug: Occlusion augmentation for event camera data
Recently, Dynamic Vision Sensors (DVSs) sparked a lot of interest due to their inherent
advantages over conventional RGB cameras. These advantages include a low latency, a …
advantages over conventional RGB cameras. These advantages include a low latency, a …
Enhanced Heart Disease Classification Using Dual Attention Mechanisms and 3D-Echo Fusion Algorithm in Echocardiogram Videos
Heart disease remains a leading cause of mortality worldwide, making early detection and
diagnosis crucial for preventing severe outcomes. Echocardiogram based classification of …
diagnosis crucial for preventing severe outcomes. Echocardiogram based classification of …
Group RandAugment: Video augmentation for action recognition
Data augmentation, as a critical strategy in deep learning, well improves the sample
diversity for network training, leading to the obvious improvement of model generalization …
diversity for network training, leading to the obvious improvement of model generalization …