67 citations · 67 across the 3 of their papers we have counts for
4 papers
StaticSegFormer: An Efficient High-Performance Semantic Segmentation Based on Static Structured Pruning
Timo Bartels, Danish Nazir, Jan Piewek +2
Structured pruning enhances the efficiency of deep neural networks (DNNs) by eliminating groups of parameters during inference. Previous methods mostly reduce computational complex…
Efficient Multi-View 3D Object Detection by Dynamic Token Selection and Fine-Tuning
Danish Nazir, Antoine Hanna-Asaad, Lucas Görnhardt +3
Existing multi-view three-dimensional (3D) object detection approaches widely adopt large-scale pre-trained vision transformer (ViT)-based foundation models as backbones, being com…
SemAttNet: Towards Attention-based Semantic Aware Guided Depth Completion
Danish Nazir, Marcus Liwicki, Didier Stricker +1
Depth completion involves recovering a dense depth map from a sparse map and an RGB image. Recent approaches focus on utilizing color images as guidance images to recover depth at…
An Efficient Semantic Segmentation Decoder for In-Car or Distributed Applications
Danish Nazir, Gowtham Sai Inti, Timo Bartels +3
Modern automotive systems leverage deep neural networks (DNNs) for semantic segmentation and operate in two key application areas: (1) In-car, where the DNN solely operates in the…