659 citations · 768 across the 5 of their papers we have counts for
5 papers
Open-Vocabulary 3D Detection via Image-level Class and Debiased Cross-modal Contrastive Learning
Yuheng Lu, Chenfeng Xu, Xiaobao Wei +4
Current point-cloud detection methods have difficulty detecting the open-vocabulary objects in the real world, due to their limited generalization capability. Moreover, it is extre…
ImageNet Training in Minutes
Yang You, Zhao Zhang, Cho-Jui Hsieh +2
Finishing 90-epoch ImageNet-1k training with ResNet-50 on a NVIDIA M40 GPU takes 14 days. This training requires 10^18 single precision operations in total. On the other hand, the…
A Metaprogramming and Autotuning Framework for Deploying Deep Learning Applications
Matthew W. Moskewicz, Ali Jannesari, Kurt Keutzer
In recent years, deep neural networks (DNNs), have yielded strong results on a wide range of applications. Graphics Processing Units (GPUs) have been one key enabling factor leadin…
How to scale distributed deep learning?
Peter H. Jin, Qiaochu Yuan, Forrest Iandola +1
Training time on large datasets for deep neural networks is the principal workflow bottleneck in a number of important applications of deep learning, such as object classification…
DenseNet: Implementing Efficient ConvNet Descriptor Pyramids
Forrest Iandola, Matt Moskewicz, Sergey Karayev +3
Convolutional Neural Networks (CNNs) can provide accurate object classification. They can be extended to perform object detection by iterating over dense or selected proposed objec…