32 citations · 100 across the 20 of their papers we have counts for
5 papers · 1 filter
BiViT: Extremely Compressed Binary Vision Transformer
Yefei He, Zhenyu Lou, Luoming Zhang +4
Model binarization can significantly compress model size, reduce energy consumption, and accelerate inference through efficient bit-wise operations. Although binarizing convolution…
Real-time End-to-End Video Text Spotter with Contrastive Representation Learning
Wejia Wu, Zhuang Li, Jiahong Li +5
Video text spotting(VTS) is the task that requires simultaneously detecting, tracking and recognizing text in the video. Existing video text spotting methods typically develop soph…
Binarizing by Classification: Is soft function really necessary?
Yefei He, Luoming Zhang, Weijia Wu +1
Binary neural networks leverage function to binarize weights and activations, which require gradient estimators to overcome its non-differentiability and will inevi…
Data-Free Quantization with Accurate Activation Clipping and Adaptive Batch Normalization
Yefei He, Luoming Zhang, Weijia Wu +1
Data-free quantization is a task that compresses the neural network to low bit-width without access to original training data. Most existing data-free quantization methods cause se…
End-to-End Video Text Spotting with Transformer
Weijia Wu, Yuanqiang Cai, Chunhua Shen +4
Recent video text spotting methods usually require the three-staged pipeline, i.e., detecting text in individual images, recognizing localized text, tracking text streams with post…