10 citations · 22 across the 24 of their papers we have counts for
5 papers · 1 filter
Global Average Feature Augmentation for Robust Semantic Segmentation with Transformers
Alberto Gonzalo Rodriguez Salgado, Maying Shen, Philipp Harzig +2
Robustness to out-of-distribution data is crucial for deploying modern neural networks. Recently, Vision Transformers, such as SegFormer for semantic segmentation, have shown impre…
SSE: Multimodal Semantic Data Selection and Enrichment for Industrial-scale Data Assimilation
Maying Shen, Nadine Chang, Sifei Liu +1
In recent years, the data collected for artificial intelligence has grown to an unmanageable amount. Particularly within industrial applications, such as autonomous vehicles, model…
Exploring Camera Encoder Designs for Autonomous Driving Perception
Barath Lakshmanan, Joshua Chen, Shiyi Lan +3
The cornerstone of autonomous vehicles (AV) is a solid perception system, where camera encoders play a crucial role. Existing works usually leverage pre-trained Convolutional Neura…
Multi-Dimensional Pruning: Joint Channel, Layer and Block Pruning with Latency Constraint
Xinglong Sun, Barath Lakshmanan, Maying Shen +3
As we push the boundaries of performance in various vision tasks, the models grow in size correspondingly. To keep up with this growth, we need very aggressive pruning techniques f…
Step Out and Seek Around: On Warm-Start Training with Incremental Data
Maying Shen, Hongxu Yin, Pavlo Molchanov +2
Data often arrives in sequence over time in real-world deep learning applications such as autonomous driving. When new training data is available, training the model from scratch u…