16 citations · 38 across the 12 of their papers we have counts for
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cs.CV2022★ 2 cited
DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training
Joya Chen, Kai Xu, Yuhui Wang +2
A standard hardware bottleneck when training deep neural networks is GPU memory. The bulk of memory is occupied by caching intermediate tensors for gradient computation in the back…
cs.CV2022★ 2 cited
Decoupling Makes Weakly Supervised Local Feature Better
Kunhong Li, Longguang Wang, Li Liu +3
Weakly supervised learning can help local feature methods to overcome the obstacle of acquiring a large-scale dataset with densely labeled correspondences. However, since weak supe…