Deep Quantization Generative Networks

•This is a pioneering work exploring quantization to accelerate and compress deep convolutional generation models.•Analyses and experiments suggest the importance of maintaining sufficient information for activation quantization.•The proposed deep quantization generative network (DQGN) quantizes both network weights and activations to low-bits.•Experiments on VAEs, GANs, style transfer, and super-resolution demonstrate the effectiveness of the proposed DQGN.