64 citations · 136 across the 13 of their papers we have counts for
7 papers
UniDistill: A Universal Cross-Modality Knowledge Distillation Framework for 3D Object Detection in Bird's-Eye View
Shengchao Zhou, Weizhou Liu, Chen Hu +2
In the field of 3D object detection for autonomous driving, the sensor portfolio including multi-modality and single-modality is diverse and complex. Since the multi-modal methods…
A Dynamic Multi-Scale Voxel Flow Network for Video Prediction
Xiaotao Hu, Zhewei Huang, Ailin Huang +2
The performance of video prediction has been greatly boosted by advanced deep neural networks. However, most of the current methods suffer from large model sizes and require extra…
Three Guidelines You Should Know for Universally Slimmable Self-Supervised Learning
Yun-Hao Cao, Peiqin Sun, Shuchang Zhou
We propose universally slimmable self-supervised learning (dubbed as US3L) to achieve better accuracy-efficiency trade-offs for deploying self-supervised models across different de…
Perceptual Conversational Head Generation with Regularized Driver and Enhanced Renderer
Ailin Huang, Zhewei Huang, Shuchang Zhou
This paper reports our solution for ACM Multimedia ViCo 2022 Conversational Head Generation Challenge, which aims to generate vivid face-to-face conversation videos based on audio…
Synergistic Self-supervised and Quantization Learning
Yun-Hao Cao, Peiqin Sun, Yechang Huang +2
With the success of self-supervised learning (SSL), it has become a mainstream paradigm to fine-tune from self-supervised pretrained models to boost the performance on downstream t…
Training Bit Fully Convolutional Network for Fast Semantic Segmentation
He Wen, Shuchang Zhou, Zhe Liang +4
Fully convolutional neural networks give accurate, per-pixel prediction for input images and have applications like semantic segmentation. However, a typical FCN usually requires l…