Monocular object 6D pose estimation is a fundamental yet challenging task in computer vision. Recently, deep learning has been proven to be capable of predicting remarkable results in this task. Existing works often a...
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Semi-supervised learning (SSL) aims to reduce reliance on labeled data. Achieving high performance often requires more complex algorithms, therefore, generic SSL algorithms are less effective when it comes to image cl...
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Currently,security-critical server programs are well protected by various defense techniques,such as Address Space Layout Randomization(ASLR),eXecute Only Memory(XOM),and Data Execution Prevention(DEP),against modern ...
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Currently,security-critical server programs are well protected by various defense techniques,such as Address Space Layout Randomization(ASLR),eXecute Only Memory(XOM),and Data Execution Prevention(DEP),against modern code-reuse attacks like Return-oriented Programming(ROP)***,in these victim programs,most syscall instructions lack the following ret instructions,which prevents attacks to stitch multiple system calls to implement advanced behaviors like launching a remote *** this kind of gadget greatly constrains the capability of code-reuse *** paper proposes a novel code-reuse attack method called Signal Enhanced Blind Return Oriented Programming(SeBROP)to address these *** SeBROP can initiate a successful exploit to server-side programs using only a stack overflow *** leveraging a side-channel that exists in the victim program,we show how to find a variety of gadgets blindly without any pre-knowledges or reading/disassembling the code ***,we propose a technique that exploits the current vulnerable signal checking mechanism to realize the execution flow control even when ret instructions are *** technique can stitch a number of system calls without returns,which is more superior to conventional ROP ***,the SeBROP attack precisely identifies many useful gadgets to constitute a Turing-complete *** attack can defeat almost all state-of-the-art defense *** SeBROP attack is compatible with both modern 64-bit and 32-bit *** validate its effectiveness,We craft three exploits of the SeBROP attack for three real-world applications,i.e.,32-bit Apache 1.3.49,32-bit ProFTPD 1.3.0,and 64-bit Nginx *** results demonstrate that the SeBROP attack can successfully spawn a remote shell on Nginx,ProFTPD,and Apache with less than 8500/4300/2100 requests,respectively.
The detection of road defects is crucial for ensuring vehicular safety and facilitating the prompt repair of roadway imperfections. Existing YOLOv8-based models face the following issues: extraction capabilities and i...
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Robust 6D object pose estimation in cluttered or occluded conditions using monocular RGB images remains a challenging task. One reason is that current pose estimation networks struggle to extract discriminative, pose-...
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Emotion recognition plays a crucial role in various fields and is a key task in natural language processing (NLP). The objective is to identify and interpret emotional expressions in text. However, traditional emotion...
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Emotion recognition plays a crucial role in various fields and is a key task in natural language processing (NLP). The objective is to identify and interpret emotional expressions in text. However, traditional emotion recognition approaches often struggle in few-shot cross-domain scenarios due to their limited capacity to generalize semantic features across different domains. Additionally, these methods face challenges in accurately capturing complex emotional states, particularly those that are subtle or implicit. To overcome these limitations, we introduce a novel approach called Dual-Task Contrastive Meta-Learning (DTCML). This method combines meta-learning and contrastive learning to improve emotion recognition. Meta-learning enhances the model’s ability to generalize to new emotional tasks, while instance contrastive learning further refines the model by distinguishing unique features within each category, enabling it to better differentiate complex emotional expressions. Prototype contrastive learning, in turn, helps the model address the semantic complexity of emotions across different domains, enabling the model to learn fine-grained emotions expression. By leveraging dual tasks, DTCML learns from two domains simultaneously, the model is encouraged to learn more diverse and generalizable emotions features, thereby improving its cross-domain adaptability and robustness, and enhancing its generalization ability. We evaluated the performance of DTCML across four cross-domain settings, and the results show that our method outperforms the best baseline by 5.88%, 12.04%, 8.49%, and 8.40% in terms of accuracy.
Multilayer graphs are an effective framework for mode ling complex systems and have garnered significant research attention. Previous studies on dense structure decomposition in multilayer graphs have generally relied...
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Space tether-net capture represents a promising solution for active space debris removal. This study proposes a gunpowder-actuated separable closing mechanism to ensure effective debris containment within the tether-n...
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Traditional autonomous driving usually requires a large number of vehicles to upload data to a central server for training. However, collecting data from vehicles may violate personal privacy as road environmental inf...
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We investigate the chiral edge states-induced Josephson current–phase relation in a graphene-based Josephson junction modulated by the off-resonant circularly polarized light and the staggered sublattice *** solving ...
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We investigate the chiral edge states-induced Josephson current–phase relation in a graphene-based Josephson junction modulated by the off-resonant circularly polarized light and the staggered sublattice *** solving the Bogoliubov–de Gennes equation,a φ_(0) Josephson junction is induced in the coaction of the off-resonant circularly polarized light and the staggered sublattice potential,which arises from the fact that the center of-mass wave vector of Cooper pair becomes finite and the opposite center of-mass wave vector to compensate is lacking in the nonsuperconducting ***,when the direction of polarization of light is changed,-φ_(0) to φ_(0) transition generates,which generalizes the concept of traditional 0–π*** findings provide a purely optical way to manipulate a phase-controllable Josephson device and guidelines for future experiments to confirm the presence of graphene-based φ_(0)Josephson junction.
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