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pro vyhledávání: '"Liu, Li"'
Over the past decade, significant progress has been made in visual object tracking, largely due to the availability of large-scale training datasets. However, existing tracking datasets are primarily focused on open-air scenarios, which greatly limit
Externí odkaz:
http://arxiv.org/abs/2409.16902
The Universal Approximation Theorem posits that neural networks can theoretically possess unlimited approximation capacity with a suitable activation function and a freely chosen or trained set of parameters. However, a more practical scenario arises
Externí odkaz:
http://arxiv.org/abs/2409.16697
This paper investigates the coexistence of positive and negative information in the context of information-epidemic dynamics on multiplex networks. In accordance with the tenets of mean field theory, we present not only the analytic solution of the p
Externí odkaz:
http://arxiv.org/abs/2409.15605
Autor:
Ying, Xinyi, Liu, Li, Lin, Zaipin, Shi, Yangsi, Wang, Yingqian, Li, Ruojing, Cao, Xu, Li, Boyang, Zhou, Shilin
Multi-frame infrared small target (MIRST) detection in satellite videos is a long-standing, fundamental yet challenging task for decades, and the challenges can be summarized as: First, extremely small target size, highly complex clutters & noises, v
Externí odkaz:
http://arxiv.org/abs/2409.12448
Motivated by the near-threshold enhancement and the dip structure around 1~GeV in the $\pi^0\pi^0$ invariant mass distribution of the process $D^0\to \pi^0\pi^0\bar{K}^0$ observed by the CLEO Collaboration, we have investigated this process by taking
Externí odkaz:
http://arxiv.org/abs/2409.09966
Monocular depth estimation aims to infer a dense depth map from a single image, which is a fundamental and prevalent task in computer vision. Many previous works have shown impressive depth estimation results through carefully designed network struct
Externí odkaz:
http://arxiv.org/abs/2409.02494
Face-based Voice Conversion (FVC) is a novel task that leverages facial images to generate the target speaker's voice style. Previous work has two shortcomings: (1) suffering from obtaining facial embeddings that are well-aligned with the speaker's v
Externí odkaz:
http://arxiv.org/abs/2409.00700
Backdoor attacks present a serious security threat to deep neuron networks (DNNs). Although numerous effective defense techniques have been proposed in recent years, they inevitably rely on the availability of either clean or poisoned data. In contra
Externí odkaz:
http://arxiv.org/abs/2408.15861
Prior-free Balanced Replay: Uncertainty-guided Reservoir Sampling for Long-Tailed Continual Learning
Even in the era of large models, one of the well-known issues in continual learning (CL) is catastrophic forgetting, which is significantly challenging when the continual data stream exhibits a long-tailed distribution, termed as Long-Tailed Continua
Externí odkaz:
http://arxiv.org/abs/2408.14976
The recent wave of foundation models has witnessed tremendous success in computer vision (CV) and beyond, with the segment anything model (SAM) having sparked a passion for exploring task-agnostic visual foundation models. Empowered by its remarkable
Externí odkaz:
http://arxiv.org/abs/2408.08315