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Found 4 papers, 1 papers with code
Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator
Real-time processing is crucial in autonomous driving systems due to the imperative of instantaneous decision-making and rapid response.
Depth-discriminative Metric Learning for Monocular 3D Object Detection
Moreover, we introduce an auxiliary head for object-wise depth estimation, which enhances depth quality while maintaining the inference time.
Dynamic Neural Network for Multi-Task Learning Searching across Diverse Network Topologies
In this paper, we present a new MTL framework that searches for structures optimized for multiple tasks with diverse graph topologies and shares features among tasks.
ADAS: A Direct Adaptation Strategy for Multi-Target Domain Adaptive Semantic Segmentation
In this paper, we present a direct adaptation strategy (ADAS), which aims to directly adapt a single model to multiple target domains in a semantic segmentation task without pretrained domain-specific models.
Ranked #3 on
Domain Adaptation
on GTAV to Cityscapes+Mapillary
