Adaptive CU Split Decision Based on Deep Learning and Multifeature Fusion for H.266/VVC

Table 4

The coding performance of the proposed algorithm compared with .

Test sequence		The proposed method
		BD-rate (%)	TS (%)
Class A1	Tango2	0.78	38.87
	FoodMarket4	0.82	39.96
	Campfire	0.89	41.55
Class A2	Catrobot1	0.92	40.14
	DaylightRoad2	0.85	39.58
	ParkRunning3	0.81	38.22
Class B	Kimono	0.78	37.51
	ParkScene	0.61	39.56
	BQTerrace	0.76	41.79
Class C	PartyScene	0.37	36.73
	RaceHorsesC	0.24	30.68
	BasketballDrill	1.25	39.21
Class D	BlowingBubbles	0.83	40.87
	RaceHorses	0.56	36.51
	BQSquare	0.58	36.67
Class E	Johnny	1.56	43.78
	FourPeople	1.34	46.51
	KristenAndSara	1.57	40.85
	Average	0.86	39.39