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Found 9 papers, 3 papers with code
Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions
Unmanned Aerial Vehicles (UAVs) are indispensable for infrastructure inspection, surveillance, and related tasks, yet they also introduce critical security challenges.
Why We Feel: Breaking Boundaries in Emotional Reasoning with Multimodal Large Language Models
Most existing emotion analysis emphasizes which emotion arises (e. g., happy, sad, angry) but neglects the deeper why.
Grasping a Handful: Sequential Multi-Object Dexterous Grasp Generation
We introduce the sequential multi-object robotic grasp sampling algorithm SeqGrasp that can robustly synthesize stable grasps on diverse objects using the robotic hand's partial Degrees of Freedom (DoF).
HA-VLN: A Benchmark for Human-Aware Navigation in Discrete-Continuous Environments with Dynamic Multi-Human Interactions, Real-World Validation, and an Open Leaderboard
Vision-and-Language Navigation (VLN) systems often focus on either discrete (panoramic) or continuous (free-motion) paradigms alone, overlooking the complexities of human-populated, dynamic environments.
SHIELD: LLM-Driven Schema Induction for Predictive Analytics in EV Battery Supply Chain Disruptions
We present SHIELD (Schema-based Hierarchical Induction for EV supply chain Disruption), a system integrating Large Language Models (LLMs) with domain expertise for EV battery supply chain risk assessment.
Human-Aware Vision-and-Language Navigation: Bridging Simulation to Reality with Dynamic Human Interactions
Vision-and-Language Navigation (VLN) aims to develop embodied agents that navigate based on human instructions.
AICAttack: Adversarial Image Captioning Attack with Attention-Based Optimization
This paper presents a novel adversarial attack strategy, AICAttack (Attention-based Image Captioning Attack), designed to attack image captioning models through subtle perturbations on images.
ACGAN-GNNExplainer: Auxiliary Conditional Generative Explainer for Graph Neural Networks
Graph neural networks (GNNs) have proven their efficacy in a variety of real-world applications, but their underlying mechanisms remain a mystery.
HybridFusion: LiDAR and Vision Cross-Source Point Cloud Fusion
First, the point cloud is divided into small patches, and a matching patch set is selected based on global descriptors and spatial distribution, which constitutes the coarse matching process.
