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Found 9 papers, 4 papers with code
CoMamba: Real-time Cooperative Perception Unlocked with State Space Models
Cooperative perception systems play a vital role in enhancing the safety and efficiency of vehicular autonomy.
CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Models
In this work, we propose CharacterFactory, a framework that allows sampling new characters with consistent identities in the latent space of GANs for diffusion models.
Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Driving
Vision-centric perception systems for autonomous driving have gained considerable attention recently due to their cost-effectiveness and scalability, especially compared to LiDAR-based systems.
V2X-DGW: Domain Generalization for Multi-agent Perception under Adverse Weather Conditions
In this paper, we propose a Domain Generalization based approach, named V2X-DGW, for LiDAR-based 3D object detection on multi-agent perception system under adverse weather conditions.
Breaking Data Silos: Cross-Domain Learning for Multi-Agent Perception from Independent Private Sources
However, the data source to train the various agents is independent and private in each company, leading to the Distribution Gap of different private data for training distinct agents in multi-agent perception system.
AdvGPS: Adversarial GPS for Multi-Agent Perception Attack
The multi-agent perception system collects visual data from sensors located on various agents and leverages their relative poses determined by GPS signals to effectively fuse information, mitigating the limitations of single-agent sensing, such as occlusion.
VehicleGAN: Pair-flexible Pose Guided Image Synthesis for Vehicle Re-identification
Vehicle Re-identification (Re-ID) has been broadly studied in the last decade; however, the different camera view angle leading to confused discrimination in the feature subspace for the vehicles of various poses, is still challenging for the Vehicle Re-ID models in the real world.
Domain Adaptation based Object Detection for Autonomous Driving in Foggy and Rainy Weather
To bridge the domain gap and improve the performance of object detection in foggy and rainy weather, this paper presents a novel framework for domain-adaptive object detection.
S2R-ViT for Multi-Agent Cooperative Perception: Bridging the Gap from Simulation to Reality
We investigate the effects of these two types of domain gaps and propose a novel uncertainty-aware vision transformer to effectively relief the Deployment Gap and an agent-based feature adaptation module with inter-agent and ego-agent discriminators to reduce the Feature Gap.
