Smart frame selection for action recognition

Author: zigc

August undefined, 2024

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 … 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 …

MGSampler: An Explainable Sampling Strategy for Video Action …

WebNov 28, 2024 · This is the source code of our CVPR 2024 paper: Understanding the Robustness of Skeleton-based Action Recognition under Adversarial Attack. A new … WebMost of the videos are captured at approximately 24-30 frames per second, each image is called a frame where you see frames per second (FPS). In our system framerate is 1.0 means it will capture ... list robert downey jr movies

A deep learning method for video‐based action recognition

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. WebSMART Frame Selection for Action Recognition Action recognition is computationally expensive. In this paper, we address the problem of frame selection to improve the … 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 … impact clothing cumberland

[2012.10671v1] SMART Frame Selection for Action …

FastPicker: Adaptive Independent Two-Stage Video-to

WebFeb 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 … WebJan 7, 2024 · We compared it against the state-of-the-art action-recognition-based frame selection methods in the literature including FastForward [10], FrameGlimpse [9], AdaFrame [8], LiteEval [7], and SMART [6] on ActivityNet-1.3 [15]. These methods try to select the most representative key-frames in which the process of learning the key frame selection ... impact clothingWebDec 19, 2024 · Abstract: Action recognition is computationally expensive. In this paper, we address the problem of frame selection to improve the accuracy of action recognition. In … impact clothing waste has on the environment

"Webfocus on the two areas within action recognition that are most relevant to our work: frame selection as well as atten-tion and relational models. Frame Selection. Selecting … " - Smart frame selection for action recognition

Smart frame selection for action recognition

DarkLight Networks for Action Recognition in the Dark

WebAbout AAAI. AAAI Officers and Committees; AAAI Staff; Bylaws of AAAI; AAAI Awards. Fellows Program; Classic Paper Award; Dissertation Award; Distinguished Service Award 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 …

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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 ... WebDec 19, 2024 · In particular, we show that selecting good frames helps in action recognition performance even in the trimmed videos domain. Recent work has successfully leveraged …

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 … WebNov 1, 2024 · Action recognition in videos has attracted growing research interests because of the explosive surveillance data in social security applications. ... for a region in clear frames, the focus of this action is likely to be the objects related but not the action itself. ... M., Sevilla-Lara, L.: SMART frame selection for action recognition. arxiv ...

WebJan 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 … 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 …

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 ...

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 ... impact club pay rentWebAug 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 impact club tenant accessWebMar 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. impact club rent managerWebMar 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. … impact co2 transport camion impact co2 frWebDec 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 … list roofing contractors in chicago ilWebJan 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 … impact cms