39 citations · 73 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 2 cited
MPI-Flow: Learning Realistic Optical Flow with Multiplane Images
Yingping Liang, Jiaming Liu, Debing Zhang +1
The accuracy of learning-based optical flow estimation models heavily relies on the realism of the training datasets. Current approaches for generating such datasets either employ…
cs.CV2020★ 32 cited
Partial FC: Training 10 Million Identities on a Single Machine
Xiang An, Xuhan Zhu, Yang Xiao +7
Training face recognition models with millions of identities is challenging because classifier storage, logit memory, and computation grow linearly with the number of classes, even…
cs.CV2020★ 39 cited
EasyQuant: Post-training Quantization via Scale Optimization
Di Wu, Qi Tang, Yongle Zhao +3
The 8 bits quantization has been widely applied to accelerate network inference in various deep learning applications. There are two kinds of quantization methods, training-based q…