83 citations · 187 across the 14 of their papers we have counts for
6 papers · 1 filter
Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
Runpei Dong, Zekun Qi, Linfeng Zhang +5
The success of deep learning heavily relies on large-scale data with comprehensive labels, which is more expensive and time-consuming to fetch in 3D compared to 2D images or natura…
Structured Knowledge Distillation Towards Efficient and Compact Multi-View 3D Detection
Linfeng Zhang, Yukang Shi, Hung-Shuo Tai +4
Detecting 3D objects from multi-view images is a fundamental problem in 3D computer vision. Recently, significant breakthrough has been made in multi-view 3D detection tasks. Howev…
Contrastive Deep Supervision
Linfeng Zhang, Xin Chen, Junbo Zhang +2
The success of deep learning is usually accompanied by the growth in neural network depth. However, the traditional training method only supervises the neural network at its last l…
Region-aware Knowledge Distillation for Efficient Image-to-Image Translation
Linfeng Zhang, Xin Chen, Runpei Dong +1
Recent progress in image-to-image translation has witnessed the success of generative adversarial networks (GANs). However, GANs usually contain a huge number of parameters, which…
PointDistiller: Structured Knowledge Distillation Towards Efficient and Compact 3D Detection
Linfeng Zhang, Runpei Dong, Hung-Shuo Tai +1
The remarkable breakthroughs in point cloud representation learning have boosted their usage in real-world applications such as self-driving cars and virtual reality. However, thes…
Wavelet Knowledge Distillation: Towards Efficient Image-to-Image Translation
Linfeng Zhang, Xin Chen, Xiaobing Tu +3
Remarkable achievements have been attained with Generative Adversarial Networks (GANs) in image-to-image translation. However, due to a tremendous amount of parameters, state-of-th…