![]() At the same time, a Transformer interactive fusion module is proposed to build long-distance dependencies and enhance semantic representation further. Specifically, we use different convolution branches for multi-scale feature extraction and aggregate them through the feature selection module adaptively. To solve this problem, this work proposes a new multi-scale feature interactive fusion network (MSIFNet) for RGBT tracking. They do not fully exploit the multi-scale information and ignore the rich contextual information among features, which limits the tracking performance to some extent. Currently, most algorithms obtain modality weights through attention mechanisms to integrate multi-modalities information. To learn more about how and for what purposes Amazon uses personal information (such as Amazon Store order history), please visit our Privacy Notice.The fusion tracking of RGB and thermal infrared image (RGBT) is paid wide attention to due to their complementary advantages. You can change your choices at any time by visiting Cookie Preferences, as described in the Cookie Notice. Click ‘Customise Cookies’ to decline these cookies, make more detailed choices, or learn more. ![]() Third parties use cookies for their purposes of displaying and measuring personalised ads, generating audience insights, and developing and improving products. This includes using first- and third-party cookies, which store or access standard device information such as a unique identifier. If you agree, we’ll also use cookies to complement your shopping experience across the Amazon stores as described in our Cookie Notice. We also use these cookies to understand how customers use our services (for example, by measuring site visits) so we can make improvements. We use cookies and similar tools that are necessary to enable you to make purchases, to enhance your shopping experiences and to provide our services, as detailed in our Cookie Notice.
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