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Found 8 papers, 1 papers with code
TGP: Two-modal occupancy prediction with 3D Gaussian and sparse points for 3D Environment Awareness
To address this issue, we propose a dual-modal prediction method based on 3D Gaussian sets and sparse points, which balances both spatial location and volumetric structural information, achieving higher accuracy in semantic occupancy prediction.
DMPA: Model Poisoning Attacks on Decentralized Federated Learning for Model Differences
In model poisoning attacks, malicious participants aim to diminish the performance of benign models by creating and disseminating the compromised model.
SafeAug: Safety-Critical Driving Data Augmentation from Naturalistic Datasets
Due to the scarcity of safety-critical data in naturalistic datasets, current approaches primarily utilize simulated or artificially generated images.
SASE: A Searching Architecture for Squeeze and Excitation Operations
Neural Architecture Search (NAS), meanwhile, is able to automate the design of neural networks and spares the numerous experiments required for an optimal architecture.
GenDDS: Generating Diverse Driving Video Scenarios with Prompt-to-Video Generative Model
Autonomous driving training requires a diverse range of datasets encompassing various traffic conditions, weather scenarios, and road types.
Enhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information
Existing cross-document event coreference resolution models, which either compute mention similarity directly or enhance mention representation by extracting event arguments (such as location, time, agent, and patient), lacking the ability to utilize document-level information.
XGBoost energy consumption prediction based on multi-system data HVAC
The energy consumption of the HVAC system accounts for a significant portion of the energy consumption of the public building system, and using an efficient energy consumption prediction model can assist it in carrying out effective energy-saving transformation.
An underwater binocular stereo matching algorithm based on the best search domain
Binocular stereo vision is an important branch of machine vision, which imitates the human eye and matches the left and right images captured by the camera based on epipolar constraints.
