3 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.CV2021★ 3 cited
DS-Net++: Dynamic Weight Slicing for Efficient Inference in CNNs and Transformers
Changlin Li, Guangrun Wang, Bing Wang +3
Dynamic networks have shown their promising capability in reducing theoretical computation complexity by adapting their architectures to the input during inference. However, their…
cs.CV2021★ 1 cited
Dynamic Slimmable Network
Changlin Li, Guangrun Wang, Bing Wang +3
Current dynamic networks and dynamic pruning methods have shown their promising capability in reducing theoretical computation complexity. However, dynamic sparse patterns on convo…
cs.CV2021
BossNAS: Exploring Hybrid CNN-transformers with Block-wisely Self-supervised Neural Architecture Search
Changlin Li, Tao Tang, Guangrun Wang +4
A myriad of recent breakthroughs in hand-crafted neural architectures for visual recognition have highlighted the urgent need to explore hybrid architectures consisting of diversif…