Smart frame selection for action recognition

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August undefined, 2024

WebMar 1, 2024 · SMART Frame Selection for Action Recognition. Article. May 2024; ... We show that the SMART frame selection consistently improves the accuracy compared to other frame selection strategies while ... WebWe show that the SMART frame selection consistently improves the accuracy compared to other frame selection strategies while reducing the computational cost by a factor of 4 to 10 times. Additionally, we show that when the primary goal is recognition performance, our selection strategy can improve over recent state-of-the-art models and frame ...

AAAI 21 SMART Frame Selection for Action Recognition ... - YouTube

WebFeb 13, 2024 · On the other hand, the computational cost of a proper and accurate human action recognition is high. In this paper, we address the challenges of the preprocessing phase, by an automated selection of representative frames from the input sequences. We extract the key features of the representative frame rather than the entire features. WebNov 1, 2024 · 25. S. N. Gowda, M. Rohrbach, and L. Sevilla-Lara, “ Smart frame selection for action recognition,” in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI Press, 2024), Vol. 35, Issue 2, pp. 1451– 1459. However, existing algorithms are limited to a specific application. These algorithms also incur additional computational ... de thi thpt 2022 mon tieng anh

Understanding the Robustness of Skeleton-based Action …

Webstimulate progress for the task of human action recogni-tion in dark videos. Currently, there are multiple mod-els that perform well for action recognition in videos shot under normal … WebWe show that the proposed frame selection consistently improves the accuracy compared to other frame selection strategies while reducing the computational cost by a factor of 4 … WebOct 1, 2024 · We showthat the SMART frame selection consistently improves the accuracy compared toother frame selection strategies while reducing the computational cost by a factorof 4 to 10 times. church and dwight net worth

DarkLight Networks for Action Recognition in the Dark

SMART Frame Selection for Action Recognition DeepAI

WebFor action recognition learning, 2D CNN-based methods are efﬁcient but may yield redundant features due to applying the same 2D convolution kernel to each frame. Recent efforts attempt to capture motion information by establishing inter-frame connections while still suffering the limited temporal receptive ﬁeld or high latency. WebApr 20, 2024 · Frame sampling is a fundamental problem in video action recognition due to the essential redundancy in time and limited computation resources. The existing sampling strategy often employs a fixed frame selection and lacks the flexibility to deal with complex variations in videos. In this paper, we present an explainable, adaptive, and effective ... church and dwight pngWebDec 19, 2024 · This paper proposes a key frame selection technique in a motion sequence of 2D frames based on gradient of optical flow to select the most important frames which … church and dwight produkte

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Smart frame selection for action recognition

WebMay 18, 2024 · In contrast to previous work, we propose a method that instead of selectingframes by considering one at a time, considers them jointly. This results in a … WebJan 8, 2024 · AAAI 21 SMART Frame Selection for Action Recognition (Long presentation) - YouTube 0:00 / 14:08 • Chapters AAAI 21 SMART Frame Selection for Action Recognition (Long …

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WebJul 1, 2024 · Abstract. Human action recognition is one of the most important topics in computer vision. Monitoring elderly people and children, smart surveillance systems and human-computer interaction are a few examples of its applications. WebApr 20, 2024 · Frame sampling is a fundamental problem in video action recognition due to the essential redundancy in time and limited computation resources. The existing sampling strategy often employs a fixed frame selection and lacks the flexibility to deal with complex variations in videos. In this paper, we present a simple, sparse, and explainable frame …

WebDec 19, 2024 · Action recognition is computationally expensive. In this paper, we address the problem of frame selection to improve the accuracy of action recognition. In … WebJan 8, 2024 · About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How YouTube works Test new features Press Copyright Contact us Creators ...

WebDec 19, 2024 · Action recognition is computationally expensive. In this paper, we address the problem of frame selection to improve the accuracy of action recognition. In particular, we … WebMay 18, 2024 · The frame selection could be trained to optimize the input for the downstream task as in [12,19] but this would introduce further complexity to controlling …

WebMar 6, 2024 · Video-based action recognition, which needs to handle temporal motion and spatial cues simultaneously, remains a challenging task. In this paper, our motivation is to address this issue by fully utilizing temporal information. Specially, a novel light-weight Voting-based Temporal Correlation (VTC) module is proposed to enhance temporal …

WebJul 7, 2024 · In this section, we first evaluate the performance obtained by using the proposed key frame selection method for the action recognition task. We use temporal segment networks (TSN) as the basic network for action recognition. We choose the UCF101 and HMDB51 datasets in the experiment. In the training process, the mini-batch … church and dwight ohioWebJan 7, 2024 · This raises the need for an effective frame selection algorithm which can either run independently or can alternatively be plugged into any 2D and 3D action recognition model in either an online or offline scenario. Our Proposal and Contributions: In this paper, we propose a novel two-stage video-to-video summarization method termed … church and dwight philanthropic foundationWebWe call the proposed frame selection SMART and we test it in combination with different backbone architectures and on multiple benchmarks (Kinetics, Something-something, UCF101). ... {SMART Frame Selection for Action Recognition}, author={Gowda, Shreyank N and Rohrbach, Marcus and Sevilla-Lara, Laura}, journal={arXiv preprint arXiv:2012.10671 ... church and dwight old fort ohioWebAug 2, 2024 · Action recognition problems have been addressed using deep learning approaches in both image and video domains. Convolutional neural networks (CNNs) have achieved state-of-the-art results in the recent decade. ... Wolf W (1996) Key frame selection by motion analysis. Proc IEEE Int Conf Acoust Speech Signal Process 2:1228–1231 church and dwight productsWebFeb 21, 2024 · Abstract. Action recognition is an important task for video understanding. Due to expensive time consumption, the conventional approaches employing the optical flow are difficult to be used for real-time purpose. Recently, the Motion Vector (MV), which can be directly extracted from the compressed video, has been introduced for action … church and dwight sodium bicarbonate sdsWebFeb 18, 2024 · Detection of fights is an important surveillance application in videos. Most existing methods use supervised binary action recognition. Since frame-level annotations are very hard to get for anomaly detection, weakly supervised learning using multiple instance learning is widely used. church and dwight revenue 2021WebMar 23, 2024 · For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame. Recent efforts attempt to capture motion information by establishing inter-frame connections while still suffering the limited temporal receptive field or high latency. … church and dwight stock performance