Current Scene Change Detection(SCD) methods are widely used in various subject areas, with detection granularity mostly limited to pixel-level. However, for certain practical applications such as garbage detection and...
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Traditional road-level topological maps cannot meet the demand for high precision navigation services required by human drivers and autonomous vehicles. Meanwhile, current enhanced lane-level topological maps with red...
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Composability allows known concepts to form newer and more complex ones. This coupling process is the research interests of Compositional Zero-Shot Learning (CZSL). The goal can be described as building a classifier f...
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Small object detection on drone-captured images is a recently popular and challenging task. From the drone’s perspective, the object scale varies significantly, and tiny objects lack distinguishable appearance inform...
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Cross-view geo-localization aims to match the query input ground-view image and the aerial-view images in the reference dataset one by one to determine the ground image's geographic location. This research is extr...
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Embodied AI, where agents accomplish specific tasks through interaction with their surrounding environment, is attracting attention in the community. As a more comprehensive and practical embodied task, visual room re...
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In this letter, we address the problem of behavior-based cooperative navigation of mobile robots usingsafe multi-agent reinforcement learning (MARL). Our work is the first to focus on cooperative navigation without in...
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Contrastive Learning (CL) has emerged as one of the most successful paradigms for unsupervised visual representation learning, yet it often depends on intensive manual data augmentations. With the rise of generative m...
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Synthetic aperture imaging(SAI) methods aim to see through dense occlusions and reconstruct the target scene behind occlusions. Traditional frame-based SAI methods,e.g., DeOccNet [1], take the occluded light field ima...
Synthetic aperture imaging(SAI) methods aim to see through dense occlusions and reconstruct the target scene behind occlusions. Traditional frame-based SAI methods,e.g., DeOccNet [1], take the occluded light field images captured by a camera array as input, and fuse them to achieve image de-occlusion.
Path planning is a critical task in autonomous driving systems that is most susceptible to real-time constraints but often demands computationally intensive mathematical solvers, two contradictory goals. This conflict...
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