Collaborative Decoder-side Motion Vector Refinement for Video Coding

Jialin Li, Zhuoyuan Li, Yao Li, Li Li, Houqiang Li

Abstract: Motion compensation prediction (MCP) is a key technology to reduce the temporal redundancy in video coding. Recently, in order to improve its efficiency, the decoder-side MCP schemes are gradually adopted in advanced video coding standards, especially the decoder-side motion vector refinement (DMVR). In DMVR, the bilateral matching scheme is used to refine the motion vector (MV) obtained from merge-based inter mode at the sub-block level, which assumes that the motion vector difference (MVD) in the two reference directions of a bi-prediction block has the symmetric property. Although the bilateral assumption can effectively reduce complexity without any extra signal, the fixed searching rules limit the motion vector accuracy. To address this limitation, we propose a collaborative decoder-side motion vector refinement (C-DMVR) framework. In C-DMVR, the sub-block-based collaborative mechanism is introduced to optimize the distortion calculation (CDC) and bilateral-based searching strategy (CSS) to avoid inaccurate searching results, respectively. In the CDC, the receptive field of the distortion function is enlarged with the collaboration of additional spatial neighbor information to assist the accurate decision of motion vector candidates. In the CSS, the coarse-to-fine candidate list derivation scheme is introduced to construct the accurate searching path with the collaboration of neighbor sub-blocks. The proposed method is implemented into the AOMedia Video 2 reference software, AV2. Experimental results show that the proposed method achieves on average 0.17%, and up to 0.60% BD-rate reduction compared to the AV2 anchor under the random access (RA) configuration, with a slight increase of time complexity on the encoding/decoding side.