Prediction Refinement with Optical Flow for Affine Motion Compensation Affine motion compensation (AMC) has been adopted in the latest working draft of the Versatile Video Coding (VVC) standard jointly developed by ITUT VCEG and ISOIEC MPEG. The AMC in the VVC working draft is implemented as a subblock based MC rather than pixelbased MC in order to reduce the memory access bandwidth and computation complexity, which loses prediction efficiency. The proposed algorithm in this paper is to improve the MC granularity by using pixelbased optical flow refinement. The affine prediction efficiency will be close to the pixelbased MC refinement without increasing external memory access. The experiment results show that on average the proposed algorithm can achieve 0.86% and 0.87% BD rate saving for random access and low delay B configurations, respectively, comparing to the VTM4.0. The BD rate saving is up to 3.10%.

Reference Picture Synthesis for Video Sequences Captured with a Monocular Moving Camera Interframe prediction plays an important role in video coding by predicting the current frame from previously encoded pictures, called reference pictures. In the case of camera motion, the content of a current frame could be very different from its reference pictures and may consequently lead to a more difficult Motion Compensation (MC). The main idea of this paper is to process the input 2D video sequence in order to estimate the 3D geometry of the scene and then employ this data to virtually synthesize geometrically compensated reference pictures. Since these virtual reference pictures are more similar to the current frame, motion estimation and consequently coding efficiency could be enhanced. The proposed method is tested over six different video sequences and around 11% bitrate reduction is achieved compared to the High Efficiency Video Coding (HEVC) standard.