Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Lu, Andong"'
Existing RGBT tracking methods often design various interaction models to perform cross-modal fusion of each layer, but can not execute the feature interactions among all layers, which plays a critical role in robust multimodal representation, due to
Externí odkaz:
http://arxiv.org/abs/2408.08827
Existing Transformer-based RGBT trackers achieve remarkable performance benefits by leveraging self-attention to extract uni-modal features and cross-attention to enhance multi-modal feature interaction and template-search correlation computation. Ne
Externí odkaz:
http://arxiv.org/abs/2408.02222
Multi-modal feature fusion as a core investigative component of RGBT tracking emerges numerous fusion studies in recent years. However, existing RGBT tracking methods widely adopt fixed fusion structures to integrate multi-modal feature, which are ha
Externí odkaz:
http://arxiv.org/abs/2405.02717
Many RGBT tracking researches primarily focus on modal fusion design, while overlooking the effective handling of target appearance changes. While some approaches have introduced historical frames or fuse and replace initial templates to incorporate
Externí odkaz:
http://arxiv.org/abs/2401.01674
Prevalent nighttime ReID methods typically combine relighting networks and ReID networks in a sequential manner, which not only restricts the ReID performance by the quality of relighting images, but also neglects the effective collaborative modeling
Externí odkaz:
http://arxiv.org/abs/2312.16246
Current RGBT tracking research relies on the complete multi-modal input, but modal information might miss due to some factors such as thermal sensor self-calibration and data transmission error, called modality-missing challenge in this work. To addr
Externí odkaz:
http://arxiv.org/abs/2312.16244
Nighttime person Re-ID (person re-identification in the nighttime) is a very important and challenging task for visual surveillance but it has not been thoroughly investigated. Under the low illumination condition, the performance of person Re-ID met
Externí odkaz:
http://arxiv.org/abs/2308.16486
Publikováno v:
In Engineering Structures 1 February 2024 300
Low-quality modalities contain not only a lot of noisy information but also some discriminative features in RGBT tracking. However, the potentials of low-quality modalities are not well explored in existing RGBT tracking algorithms. In this work, we
Externí odkaz:
http://arxiv.org/abs/2011.07188
RGBT tracking has attracted increasing attention since RGB and thermal infrared data have strong complementary advantages, which could make trackers all-day and all-weather work. However, how to effectively represent RGBT data for visual tracking rem
Externí odkaz:
http://arxiv.org/abs/2011.07189