Geometric Partitioning Mode with Affine Prediction in Video Coding

Kai Zhang, Zhipin Deng, Li Zhang

Abstract: Geometric partitioning mode (GPM) splits a coding block into two partitions, which can be non-rectangular, separated by a straight splitting line. Two uni inter-predictions generated by translational motion compensation (TMC) for the two GPM partitions are blended to obtain the final prediction. With a promising coding gain, GPM has been adopted in versatile video coding (VVC). Beyond VVC, enhanced compression model (ECM) introduces several extensions on GPM, but GPM still cannot deal with affine motions well. This paper presents a method of GPM with affine prediction (GPM-affine). A GPM partition can be predicted by affine motion compensation (AMC) or TMC, indicated by a flag. A GPM partition predicted by AMC can be blended with the other GPM partition predicted by AMC, TMC, or intra-prediction. Experimental results show that GPM-affine provides an average luma BD-rate saving of 0.19% compared to ECM-10.0 in random access configurations under the common test condition, with a negligible running time change. On sequences with rich affine motions, 1% coding gain in average is observed. Currently, GPM-affine is under study in exploration experiments (EE) for ECM in JVET.