19 citations · 21 across the 3 of their papers we have counts for
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cs.CV2024
SDformer: Efficient End-to-End Transformer for Depth Completion
Jian Qian, Miao Sun, Ashley Lee +3
Depth completion aims to predict dense depth maps with sparse depth measurements from a depth sensor. Currently, Convolutional Neural Network (CNN) based models are the most popula…
cs.CV2023★ 19 cited
FastPillars: A Deployment-friendly Pillar-based 3D Detector
Sifan Zhou, Zhi Tian, Xiangxiang Chu +7
The deployment of 3D detectors strikes one of the major challenges in real-world self-driving scenarios. Existing BEV-based (i.e., Bird Eye View) detectors favor sparse convolution…
cs.CV2018★ 2 cited
FotonNet: A HW-Efficient Object Detection System Using 3D-Depth Segmentation and 2D-DNN Classifier
Gurjeet Singh, Sun Miao, Shi Shi +1
Object detection and classification is one of the most important computer vision problems. Ever since the introduction of deep learning \cite{krizhevsky2012imagenet}, we have witne…