US 12,293,532 B2
Image processing method, apparatus, and device, path planning method, apparatus, and device, and storage medium
Yonggen Ling, Guangdong (CN); Wanchao Chi, Guangdong (CN); Chong Zhang, Guangdong (CN); Shenghao Zhang, Guangdong (CN); Zhengyou Zhang, Guangdong (CN); Zejian Yuan, Guangdong (CN); Ang Li, Guangdong (CN); and Zidong Cao, Guangdong (CN)
Assigned to Tencent Technology (Shenzhen) Company Limited, Shenzhen (CN)
Filed by Tencent Technology (Shenzhen) Company Limited, Guangdong (CN)
Filed on Feb. 25, 2022, as Appl. No. 17/680,515.
Application 17/680,515 is a continuation of application No. PCT/CN2020/128292, filed on Nov. 12, 2020.
Claims priority of application No. 202010141219.9 (CN), filed on Mar. 4, 2020.
Prior Publication US 2022/0180543 A1, Jun. 9, 2022
Int. Cl. G06T 7/55 (2017.01); G05D 1/00 (2024.01); G06T 3/40 (2024.01); G06T 7/521 (2017.01)
CPC G06T 7/55 (2017.01) [G05D 1/0248 (2013.01); G06T 3/40 (2013.01); G06T 7/521 (2017.01); G06T 2207/10024 (2013.01); G06T 2207/10028 (2013.01); G06T 2207/20016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01); G06T 2207/30252 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of depth map completion, comprising:
receiving, by processing circuitry of an information processing apparatus, a color map and a sparse depth map that are corresponding to a target scenario;
adjusting, by the processing circuitry of the information processing apparatus, resolutions of the color map and the sparse depth map to generate n pairs of color maps and sparse depth maps of n different resolutions, each pair including one color map and one sparse depth map of a respective same resolution of the n different resolutions, n being a positive integer greater than 1;
processing, by the processing circuitry of the information processing apparatus, the n pairs of the color maps and the sparse depth maps to generate n prediction result maps using a cascade hourglass network including n levels of hourglass networks cascaded together, each of the n pairs being an input to a respective one of the n levels of the hourglass networks to generate the respective one of the n prediction result maps, the n prediction result maps each including a dense depth map of the same resolution as the corresponding pair; and
generating, by the processing circuitry of the information processing apparatus, a final dense depth map corresponding to the target scenario according to the dense depth maps of the n prediction result maps, wherein
each input to a first one of the n levels of hourglass networks consists of a first pair of a first color map and a first sparse depth map,
the first pair is one of the n pairs of color maps and sparse depth maps, and
each input to the first one of the n levels of hourglass networks is of a first resolution.