TLVC: Temporal Bit-rate Allocation for Learned Video Compression

Yifan Zhang, Meiqin Liu, Chenming Xu, Qi Tang, Chao Yao, Yao Zhao

Abstract: Most of the existing neural video compression methods adopt the hybrid coding framework, which only focus on the motion and residual coding of adjacent frames and ignore the long-term inter-frame dependency and bit-rate allocation. To address the shortcoming, we propose a temporal bit-rate allocation strategy for learned video compression (TLVC). Specifically, Motion-driven Temporal Gate (MTG) is designed to yield temporal bit-rate coefficient by considering the impact of residual coding on subsequent motion estimation. Sequentially, Texture-conditioned Spatial Gate (TSG) is proposed to take the generated coefficient to guide the residual compression with different bit-rate. Experimental results demonstrate that TLVC can achieve effective bit-rate allocation compared with the traditional codec H.266/VVC (VTM-13.2) of low delay p-frame (LDP) configuration.