13 citations · 25 across the 7 of their papers we have counts for
6 papers · 1 filter
Razor SNN: Efficient Spiking Neural Network with Temporal Embeddings
Yuan Zhang, Jian Cao, Ling Zhang +3
The event streams generated by dynamic vision sensors (DVS) are sparse and non-uniform in the spatial domain, while still dense and redundant in the temporal domain. Although spiki…
Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with Uncertainty
Yuan Zhang, Weihua Chen, Yichen Lu +3
Knowledge distillation is an effective paradigm for boosting the performance of pocket-size model, especially when multiple teacher models are available, the student would break th…
Masked Distillation with Receptive Tokens
Tao Huang, Yuan Zhang, Shan You +4
Distilling from the feature maps can be fairly effective for dense prediction tasks since both the feature discriminability and localization priors can be well transferred. However…
RAPQ: Rescuing Accuracy for Power-of-Two Low-bit Post-training Quantization
Hongyi Yao, Pu Li, Jian Cao +3
We introduce a Power-of-Two low-bit post-training quantization(PTQ) method for deep neural network that meets hardware requirements and does not call for long-time retraining. Powe…
A free lunch from ViT:Adaptive Attention Multi-scale Fusion Transformer for Fine-grained Visual Recognition
Yuan Zhang, Jian Cao, Ling Zhang +4
Learning subtle representation about object parts plays a vital role in fine-grained visual recognition (FGVR) field. The vision transformer (ViT) achieves promising results on com…
AdaPruner: Adaptive Channel Pruning and Effective Weights Inheritance
Xiangcheng Liu, Jian Cao, Hongyi Yao +2
Channel pruning is one of the major compression approaches for deep neural networks. While previous pruning methods have mostly focused on identifying unimportant channels, channel…