Zobrazeno 1 - 10
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pro vyhledávání: '"WANG, Yonghui"'
Over the past few years, the advancement of Multimodal Large Language Models (MLLMs) has captured the wide interest of researchers, leading to numerous innovations to enhance MLLMs' comprehension. In this paper, we present AdaptVision, a multimodal l
Externí odkaz:
http://arxiv.org/abs/2408.16986
In video lane detection, there are rich temporal contexts among successive frames, which is under-explored in existing lane detectors. In this work, we propose LaneTCA to bridge the individual video frames and explore how to effectively aggregate the
Externí odkaz:
http://arxiv.org/abs/2408.13852
Shadow detection is a fundamental and challenging task in many computer vision applications. Intuitively, most shadows come from the occlusion of light by the object itself, resulting in the object and its shadow being contiguous (referred to as the
Externí odkaz:
http://arxiv.org/abs/2408.03521
The advent of Large Multimodal Models (LMMs) has sparked a surge in research aimed at harnessing their remarkable reasoning abilities. However, for understanding text-rich images, challenges persist in fully leveraging the potential of LMMs, and exis
Externí odkaz:
http://arxiv.org/abs/2404.09797
The integration of local elements into shape contours is critical for target detection and identification in cluttered scenes. Previous studies have shown that observers can learn to use image regularities for contour integration and target identific
Externí odkaz:
http://arxiv.org/abs/2403.11516
In the field of document understanding, significant advances have been made in the fine-tuning of Multimodal Large Language Models (MLLMs) with instruction-following data. Nevertheless, the potential of text-grounding capability within text-rich scen
Externí odkaz:
http://arxiv.org/abs/2311.13194
Single-image shadow removal is a significant task that is still unresolved. Most existing deep learning-based approaches attempt to remove the shadow directly, which can not deal with the shadow well. To handle this issue, we consider removing the sh
Externí odkaz:
http://arxiv.org/abs/2311.00455
Segment anything model (SAM) has achieved great success in the field of natural image segmentation. Nevertheless, SAM tends to consider shadows as background and therefore does not perform segmentation on them. In this paper, we propose ShadowSAM, a
Externí odkaz:
http://arxiv.org/abs/2305.16698
Publikováno v:
Shipin Kexue, Vol 45, Iss 12, Pp 101-108 (2024)
In this study, the stability of cow’s milk with fat replacement by soybean oil bodies (SOB) was investigated under different environmental conditions. Moreover, the effect of replacing milk fat with SOB or anhydrous milk fat (AMF) on the stability
Externí odkaz:
https://doaj.org/article/2dfa1b56bd724ffe91d6cf55907f7587
